Soil microorganisms play a vital role in increasing the availability of phosphorus (P) for plants through mineralization of organic P and solubilization of precipitated P compounds. In this two-year study, we analyzed several P-solubilizing microorganisms (PSMs) of the genus Bacillus and their consortiums for the ability to release soluble P from apatite concentrates of various grinding degrees using ryegrass (Lolium multiflorum Lam.) as a model plant. The effects were accessed by analyzing plant growth and nutrient assimilation. The greatest effect on root system development and plant biomass accumulation (dry weight) was observed for the apatite concentrate of standard grinding in combination with Bacillus megaterium BI14 and Bacillus subtilis BI2 and Bacillus velezensis BS89 strains. Although the introduction of apatite concentrates led to an increase in the content of total strontium in soil, the levels of strontium did not exceed the maximum allowable concentration, and the accumulation of mobile strontium by plants was unchanged; importantly, the use of tested PSMs led to a decrease in the strontium content in the green biomass of ryegrass. Our results indicate that biologized apatite concentrates in combination with PSMs represent promising fertilizers that can provide a source of soluble P to be readily assimilated by plants.

Identification of promoter sequences in the eukaryotic genome, by computer methods, is an important task of bioinformatics. However, this problem has not been solved since the best algorithms have a false positive probability of 10⁻³–10⁻⁴ per nucleotide. As a result of full genome analysis, there may be more false positives than annotated gene promoters. The probability of a false positive should be reduced to 10⁻⁶–10⁻⁸ to reduce the number of false positives and increase the reliability of the prediction. The method for multi alignment of the promoter sequences was developed. Then, mathematical methods were developed for calculation of the statistically important classes of the promoter sequences. Five promoter classes, from the rice genome, were created. We developed promoter classes to search for potential promoter sequences in the rice genome with a false positive number less than 10⁻⁸ per nucleotide. Five classes of promoter sequences contain 1740, 222, 199, 167 and 130 promoters, respectively. A total of 145,277 potential promoter sequences (PPSs) were identified. Of these, 18,563 are promoters of known genes, 87,233 PPSs intersect with transposable elements, and 37,390 PPSs were found in previously unannotated sequences. The number of false positives for a randomly mixed rice genome is less than 10⁻⁸ per nucleotide. The method developed for detecting PPSs was compared with some previously used approaches. The developed mathematical method can be used to search for genes, transposable elements, and transcript start sites in eukaryotic genomes.

The exact identification of promoter sequences remains a serious problem in computational biology, as the promoter prediction algorithms under development continue to produce false-positive results. Therefore, to fully assess the validity of predicted sequences, it is necessary to perform a comprehensive test of their properties, such as the presence of downstream transcribed DNA regions behind them, or chromatin accessibility for transcription factor binding. In this paper, we examined the promoter sequences of chromosome 1 of the rice Oryza sativa genome from the Database of Potential Promoter Sequences predicted using a mathematical algorithm based on the derivation and calculation of statistically significant promoter classes. In this paper TATA motifs and cis-regulatory elements were identified in the predicted promoter sequences. We also verified the presence of potential transcription start sites near the predicted promoters by analyzing CAGE-seq data. We searched for unannotated transcripts behind the predicted sequences by de novo assembling transcripts from RNA-seq data. We also examined chromatin accessibility in the region of the predicted promoters by analyzing ATAC-seq data. As a result of this work, we identified the predicted sequences that are most likely to be promoters for further experimental validation in an in vivo or in vitro system.

The technologies of genome editing and synthetic biology are becoming more and more accessible today and, in combination with the application of artificial intelligence in biotechnology, especially powerful. A feature of today’s stage is the rapidly changing landscape of engineering biological systems, which requires revision and updating of the biosafety framework. The proposed new oversight measures are as follows: а) screening for DNA synthesis orders and sequences of concern; b) environmental metagenome sequencing to search for synthetic organisms [1]. At the same time, DNA ‘printers’ are appeared on the market today, that blurs the boundaries of access to synthetic DNA. It is significant that no government currently requires screening or regulates it, and this system works on a benevolent basis. Additionally environmental surveillance requires for a long time to define base line. With the new scale of human activity, new social risks also arise: new forms of discrimination and inequality, confidentiality of personal data in biotechnology projects, multiplication of biotechnology and artificial intelligence risks. Thus, the idea of “responsible researches and innovation” (RRI) [2], and trend to address safety early at the concept stage — “Safe by design” have come into the focus. A number of RRI principles can be formulated at the proof concept stage for a genome- edited project: benefits for most citizens; transparency, the public comment cycle prior to the start of the experiments; responsibility, precautions, liability; justice, redress; well-being, social good.

The identification of risks associated with novel agricultural products of plant origin obtained via genome editing is an important aspect of genetic engineering. An extensive discussion is currently ongoing worldwide to clarify the similarities and differences between the “old” risks of “classic” GM plants and the “new” ones associated with genome editing, the lack of existing methods for identification and assessment of new risks. We propose here the concept of “safe by design” as applied to protection that is a new interesting tool that introduces good known standards of safety into plant bioengineering. This approach states that design options are identified to minimize or prevent risks and off-target of genome editing at the concept stage. The correlation between experimentally determined and in silico predicted off-target gRNA activity is a major challenge in the CRISPR system application. Today the most studies are focused on efficiency of gRNA design, while we pay attention specifically to the bioinformatics search and study of potential promoters, as the potential risk associates with a possible unplanned change in the transcriptional activity of promoters. We conveyed these strategies in the form of a risk assessment framework for regulation of new genetic technologies.