The auxin-inducible degron (AID) system is a promising tool for dynamic protein degradation. In mammalian cells, this approach has become indispensable to study fundamental molecular functions, such as replication, chromatin dynamics, or transcription, which are otherwise difficult to dissect. We present evaluation of the two prominent AID systems based on OsTIR1 and AtAFB2 auxin receptor F-box proteins (AFBs). We analyzed degradation dynamics of cohesin/condensin complex subunits in mouse embryonic stem cells (Rad21, Smc2, Ncaph, and Ncaph2) and human haploid HAP1 line (RAD21, SMC2). Double antibiotic selection helped achieve high homozygous AID tagging of an endogenous gene for all genes using CRISPR/Cas9. We found that the main challenge for successful protein degradation is obtaining cell clones with high and stable AFB expression levels due to the mosaic expression of AFBs. AFB expression from a transgene tends to decline with passages in the absence of constant antibiotic selection, preventing epigenetic silencing of a transgene, even at the AAVS1 safe-harbor locus. Comparing two AFBs, we found that the OsTIR1 system showed weak dynamics of protein degradation. At the same time, the AtAFB2 approach was very efficient even in random integration of AFB-expressed transgenes. Other factors such as degradation dynamics and low basal depletion were also in favor of the AtAFB2 system.

The association between pre-harvest sprouting (PHS) and seed coat color has long been recognized. Red-grained wheats generally exhibit greater PHS resistance compared to white-grained wheat, although variability in PHS resistance exists within red-grained varieties. Here, we conducted a genome-wide association study on a panel consisting of red-grained wheat varieties, aimed at uncovering genes that modulate PHS resistance and red color components of seed coat using digital image processing. Twelve loci associated with PHS traits were identified, nine of which were described for the first time. Genetic loci marked by SNPs AX-95172164 (chromosome 1B) and AX-158544327 (chromosome 7D) explained approximately 25% of germination index variance, highlighting their value for breeding PHS-resistant varieties. The most promising candidate gene for PHS resistance was TraesCS6B02G147900, encoding a protein involved in aleurone layer morphogenesis. Twenty-six SNPs were significantly associated with grain color, independently of the known Tamyb10 gene. Most of them were related to multiple color characteristics. Prioritization of genes within the revealed loci identified TraesCS1D03G0758600 and TraesCS7B03G1296800, involved in the regulation of pigment biosynthesis and in controlling pigment accumulation. In conclusion, our study identifies new loci associated with grain color and germination index, providing insights into the genetic mechanisms underlying these traits.

Many plants and animals have symbiotic relationships with microorganisms, including bacteria. The interactions between bacteria and their hosts result in different outcomes for the host organism. The outcome can be neutral, harmful or have beneficial effects for participants. Remarkably, these relationships are not static, as they change throughout an organism’s lifetime and on an evolutionary scale. One of the structures responsible for relationships in bacteria is O-antigen. Depending on the characteristics of its components, the bacteria can avoid the host’s immune response or establish a mutualistic relationship with it. O-antigen is a key component in Gram-negative bacteria’s outer membrane. This component facilitates interaction between the bacteria and host immune system or phages. The variability of the physical structure is caused by the genomic variability of genes encoding O-antigen synthesis components. The genes and pathways of O-polysaccharide (OPS) synthesis were intensively investigated mostly for Enterobacteriaceae species. Considering high genetic and molecular diversity of this structure even between strains, these findings may not have caught the entire variety possibly presented in non-model species. The current study presents a comparative analysis of genes associated with O-antigen synthesis in bacteria of the Oxalobacteraceae family. In contrast to existing studies based on PCR methods, we use a bioinformatics approach and compare O- anti gens at the level of clusters rather than individual genes. We found that the O-antigen genes of these bacteria are represented by several clusters located at a distance from each other. The greatest similarity of the clusters is observed within individual bacterial genera, which is explained by the high variability of O-antigens. The study describes similarities of OPS genes inherent to the family as a whole and also considers individual unique cases of O-antigen genetic variability inherent to individual bacteria.

Currently, the breeding of agricultural plants is increasingly based on the use of molecular biological data on genetic sequences, which makes it possible to significantly accelerate the breeding process, create new plant varieties through genomic editing. These data have a large volume, variety and require a large amount of resources, both labor and computing, to analyze the costs. Data analysis of such volume and complexity can be effective only when using modern bioinformatics methods, which include algorithms for identifying genes, predicting their function, and evaluating the effect of mutation on plant phenotype. Such an analysis has recently become impossible without the use of integrated software systems that solve problems of different levels by executing computational pipelines. The paper describes the CropGene software package developed for the comprehensive analysis of genomic and transcriptomic data of agricultural plants. CropGene includes several blocks of bioinformatic analysis, such as analysis of gene variations, assembly of genomes and transcriptomes, as well as annotation of genes and proteins. CropGene implements new methods for analyzing long non-coding RNAs, protein domains, searching and analyzing polymorphisms, and genomewide association research. CropGene has a user-friendly interface and supports working with various types of data, which greatly simplifies its use for researchers who do not have deep knowledge in the field of bioinformatics. The paper provides examples of the use of CropGene for the analysis of agricultural organisms such as Solanum tuberosum and Zea mays. With CropGene, genetic markers have been identified that explain up to 50 % of the variability in seed color parameters; potential genes that may become promising material for producing potato varieties; more than 100 thousand new long non-coding RNAs. Orthogroups were also found, the domain structure of which shows a marked similarity with the domain architecture of characteristic secreted A2 phospholipases. Thus, CropGene is an important tool for scientists and practitioners working in the field of agrobiotechnology and plant genetics.