Data augmentation with generative models improves detection of Non-B DNA structures.

Non-B DNA structures, or flipons, are important functional elements that regulate a large spectrum of cellular programs. Experimental technologies for flipon detection are limited to the subsets that are active at the time of an experiment and cannot capture whole-genome functional set. Thus, the task of generating reliable whole-genome annotations of non-B DNA structures is put on deep learning models, however their quality depends on the available experimental data for training.

Z-DNA formation in promoters conserved between human and mouse are associated with increased transcription reinitiation rates.

A long-standing question concerns the role of Z-DNA in transcription. Here we use a deep learning approach DeepZ that predicts Z-flipons based on DNA sequence, structural properties of nucleotides and omics data. We examined Z-flipons that are conserved between human and mouse genomes after generating whole-genome Z-flipon maps and then validated them by orthogonal approaches based on high resolution chemical mapping of Z-DNA and the transformer algorithm Z-DNABERT.

Research of Russian physicians' opinions on tuberculosis pharmacogenetics.

Background: There is currently no widespread implementation of pharmacogenetic testing (PGx) methods in the practice of phthisiology service.

Objective: The aim of this study is to determine how informed and prepared phthisiologists, residents, and postgraduate students of the Russian Medical Academy of Continuing Professional Education (RMACPE, Moscow) use PGx techniques in their work to improve treatment safety, predict the occurrence of adverse reactions (ADRs), and personalize therapy.

Methods: A survey was conducted among phthisiologists (n = 314) living in different regions of the Russian Federation and studying at RMACPE, such as residents and post-graduate students (n = 185).

Z-flipon variants reveal the many roles of Z-DNA and Z-RNA in health and disease.

Identifying roles for Z-DNA remains challenging given their dynamic nature. Here, we perform genome-wide interrogation with the DNABERT transformer algorithm trained on experimentally identified Z-DNA forming sequences (Z-flipons). The algorithm yields large performance enhancements (F1 = 0.

Unsupervised domain adaptation methods for cross-species transfer of regulatory code signals.

Due to advances in NGS technologies whole-genome maps of various functional genomic elements were generated for a dozen of species, however experiments are still expensive and are not available for many species of interest. Deep learning methods became the state-of-the-art computational methods to analyze the available data, but the focus is often only on the species studied. Here we take advantage of the progresses in Transfer Learning in the area of Unsupervised Domain Adaption (UDA) and tested nine UDA methods for prediction of regulatory code signals for genomes of other species.

Conserved microRNAs and Flipons Shape Gene Expression during Development by Altering Promoter Conformations.

The classical view of gene regulation draws from prokaryotic models, where responses to environmental changes involve operons regulated by sequence-specific protein interactions with DNA, although it is now known that operons are also modulated by small RNAs. In eukaryotes, pathways based on microRNAs (miR) regulate the readout of genomic information from transcripts, while alternative nucleic acid structures encoded by flipons influence the readout of genetic programs from DNA. Here, we provide evidence that miR- and flipon-based mechanisms are deeply connected.

DeepZ: A Deep Learning Approach for Z-DNA Prediction.

Here we describe an approach that uses deep learning neural networks such as CNN and RNN to aggregate information from DNA sequence; physical, chemical, and structural properties of nucleotides; and omics data on histone modifications, methylation, chromatin accessibility, and transcription factor binding sites and data from other available NGS experiments. We explain how with the trained model one can perform whole-genome annotation of Z-DNA regions and feature importance analysis in order to define key determinants for functional Z-DNA regions.

A survey of physician opinions in Russia in the field of pharmacogenetics of cardiovascular disease.

To study the readiness of Russian physicians with experience and younger physicians undergoing clinical residency and postgraduate education to apply pharmacogenetic testing in their clinical practice. The sociological study involved physicians (n = 378) living in different regions of the Russian Federation, as well as residents and graduate students (n = 185) of the Russian Medical Academy of Continuing Professional Medical Education. The survey consisted of 35 questions, and 23 were created on the online platform of professional surveys, Testograf.

Z-RNA and the Flipside of the SARS Nsp13 Helicase: Is There a Role for Flipons in Coronavirus-Induced Pathology?

We present evidence suggesting that the severe acute respiratory syndrome (SARS) coronavirus non-structural protein 13 (Nsp13) modulates the Z-RNA dependent regulated cell death pathways . We show that Z-prone sequences [called flipons] exist in coronavirus and provide a signature (Z-sig) that enables identification of the animal viruses from which the human pathogens arose. We also identify a potential RIP Homology Interaction Motif (RHIM) in the helicase Nsp13 that resembles those present in proteins that initiate Z-RNA-dependent cell death through interactions with the Z-RNA sensor protein ZBP1.

Mono a Mano: ZBP1's Love-Hate Relationship with the Kissing Virus.

Z-DNA binding protein (ZBP1) very much represents the nuclear option. By initiating inflammatory cell death (ICD), ZBP1 activates host defenses to destroy infectious threats. ZBP1 is also able to induce noninflammatory regulated cell death via apoptosis (RCD).

Special Issue: A, B and Z: The Structure, Function and Genetics of Z-DNA and Z-RNA.

It is now difficult to believe that a biological function for the left-handed Z-DNA and Z-RNA conformations was once controversial. The papers in this Special Issue, "Z-DNA and Z-RNA: from Physical Structure to Biological Function", are based on presentations at the ABZ2021 meeting that was held virtually on 19 May 2021 and provide evidence for several biological functions of these structures. The first of its kind, this international conference gathered over 200 scientists from many disciplines to specifically address progress in research involving Z-DNA and Z-RNA.

Comprehensive analysis of cancer breakpoints reveals signatures of genetic and epigenetic contribution to cancer genome rearrangements.

Understanding mechanisms of cancer breakpoint mutagenesis is a difficult task and predictive models of cancer breakpoint formation have to this time failed to achieve even moderate predictive power. Here we take advantage of a machine learning approach that can gather important features from big data and quantify contribution of different factors. We performed comprehensive analysis of almost 630,000 cancer breakpoints and quantified the contribution of genomic and epigenomic features-non-B DNA structures, chromatin organization, transcription factor binding sites and epigenetic markers.

Deep learning approach for predicting functional Z-DNA regions using omics data.

Computational methods to predict Z-DNA regions are in high demand to understand the functional role of Z-DNA. The previous state-of-the-art method Z-Hunt is based on statistical mechanical and energy considerations about B- to Z-DNA transition using sequence information. Z-DNA CHiP-seq experiment results showed little overlap with Z-Hunt predictions implying that sequence information only is not sufficient to explain emergence of Z-DNA at different genomic locations.

Interethnic differences in the prevalence of main cardiovascular pharmacogenetic biomarkers.

The aim of this study was to determine the prevalence of , , , , and genes polymorphisms among residents of the Volga region (Chuvash and Mari) and northern Caucasus (Kabardins and Ossetians). The study involved 845 apparently healthy volunteers of both sexes of the four different ethnic groups living in the Russian Federation: 238 from the Chuvash ethnic group, 206 Mari, 157 Kabardins and 244 Ossetians. Significant differences were identified in allele frequency of , , , , and genes polymorphisms between the Chuvash and Kabardins, Chuvash and Ossetians, Mari and Kabardians, Mari and Ossetians.

Tissue-specific impact of stem-loops and quadruplexes on cancer breakpoints formation.

Background: Chromosomal rearrangements are the typical phenomena in cancer genomes causing gene disruptions and fusions, corruption of regulatory elements, damage to chromosome integrity. Among the factors contributing to genomic instability are non-B DNA structures with stem-loops and quadruplexes being the most prevalent. We aimed at investigating the impact of specifically these two classes of non-B DNA structures on cancer breakpoint hotspots using machine learning approach.

Recognition of 3'-end L1, Alu, processed pseudogenes, and mRNA stem-loops in the human genome using sequence-based and structure-based machine-learning models.

The role of 3'-end stem-loops in retrotransposition was experimentally demonstrated for transposons of various species, where LINE-SINE retrotransposons share the same 3'-end sequences, containing a stem-loop. We have discovered that 62-68% of processed pseduogenes and mRNAs also have 3'-end stem-loops. We investigated the properties of 3'-end stem-loops of human L1s, Alus, processed pseudogenes and mRNAs that do not share the same sequences, but all have 3'-end stem-loops.

Conserved 3' UTR stem-loop structure in L1 and Alu transposons in human genome: possible role in retrotransposition.

Background: In the process of retrotransposition LINEs use their own machinery for copying and inserting themselves into new genomic locations, while SINEs are parasitic and require the machinery of LINEs. The exact mechanism of how a LINE-encoded reverse transcriptase (RT) recognizes its own and SINE RNA remains unclear. However it was shown for the stringent-type LINEs that recognition of a stem-loop at the 3'UTR by RT is essential for retrotransposition.

[Modeling of mechanochemical DNA cleavage by action of ultrasound].

This study offers a simulation of the stretching dynamics of a double-stranded DNA fragment in the high-gradient flow of fluid near collapsing cavitation bubbles. Calculated profiles of elastic tension along the model of a polymer fragment were used to estimate the rates of mechanochemical cleavage at different positions of DNA restriction fragments. The resulting cleavage rate profiles are qualitatively consistent with the experimentally observed profiles of ultrasonic cleavage rates of DNA restriction fragments, which are position-dependent.

Impact of constitutional copy number variants on biological pathway evolution.

Background: Inherited Copy Number Variants (CNVs) can modulate the expression levels of individual genes. However, little is known about how CNVs alter biological pathways and how this varies across different populations. To trace potential evolutionary changes of well-described biological pathways, we jointly queried the genomes and the transcriptomes of a collection of individuals with Caucasian, Asian or Yoruban descent combining high-resolution array and sequencing data.

Quartet decomposition server: a platform for analyzing phylogenetic trees.

Background: The frequent exchange of genetic material among prokaryotes means that extracting a majority or plurality phylogenetic signal from many gene families, and the identification of gene families that are in significant conflict with the plurality signal is a frequent task in comparative genomics, and especially in phylogenomic analyses. Decomposition of gene trees into embedded quartets (unrooted trees each with four taxa) is a convenient and statistically powerful technique to address this challenging problem. This approach was shown to be useful in several studies of completely sequenced microbial genomes.