Journal of Applied Genetics最新文献

Strigolactones (SLs) are plant hormones that play a crucial role in regulating various aspects of plant architecture, such as shoot and root branching. However, the knowledge of SL-responsive genes and transcription factors (TFs) that control the shaping of plant architecture remains elusive. Here, transcriptomic analysis was conducted using the SL-insensitive barley mutant hvd14.d (carried mutation in SL receptor DWARF14, HvD14) and its wild-type (WT) to unravel the differences in gene expression separately in root and shoot tissues. This approach enabled us to select more than six thousand SL-dependent genes that were exclusive to each studied organ or not tissue-specific. The data obtained, along with in silico analyses, found several TFs that exhibited changed expression between the analyzed genotypes and that recognized binding sites in promoters of other identified differentially expressed genes (DEGs). In total, 28 TFs that recognize motifs over-represented in DEG promoters were identified. Moreover, nearly half of the identified TFs were connected in a single network of known and predicted interactions, highlighting the complexity and multidimensionality of SL-related signalling in barley. Finally, the SL control on the expression of one of the identified TFs in HvD14- and dose-dependent manners was proved. Obtained results bring us closer to understanding the signalling pathways regulating SL-dependent plant development.

Pedigree indices (PI) and genomically enhanced breeding values (GBV) of Polish Holstein-Friesian heifers were compared with their future performance. Phenotypes of 15,794 cows from 294 herds were analyzed. The traits evaluated included milk, fat and protein yield, somatic cell score (SCC), stature, overall udder and feet and legs score, heifer conception rate, and longevity. PI and GBV were from official evaluation systems, and performance records were adjusted for non-genetic effects. Correlations between breeding values and adjusted phenotypes were analyzed. Additionally, cows within each herd were divided into quartiles based on their breeding values, and the performance of cows from the top and bottom quartiles was compared. For production traits, similar analyses were conducted separately for high and low milk-producing herds to check for possible genotype by environment interaction. The analyses confirmed the significant correlation between breeding values and cow performance. Incorporating genomic information into PI significantly improved the predictive accuracy for milk, fat, and protein yields, as well as for SCC and stature, with increases ranging from 34 to 64%. Comparisons of cows' performance from the top and bottom quartiles supported these observations for all these traits except protein yield, with differences in performance being 43-92% greater when cows were ranked by GBV instead of PI. In a more productive environment, greater differences in performance were found between the top and bottom quartiles. These findings suggest that Polish breeders can enhance the outcomes of their breeding decisions by using GBV instead of PI. This change offers particular benefits in improving the predictability of future performance for the most economically important traits such as milk yield, fat yield, protein yield, somatic cell score, and stature.

Europe is highly dependent on soybean meal imports and anticipates an increase of domestic plant protein production. Ongoing climate change resulted in northward shift of plant hardiness zones, enabling spring-sowing of freezing-sensitive crops, including soybean. However, it requires efficient reselection of germplasm adapted to relatively short growing season and long-day photoperiod. In the present study, a PCR array has been implemented, targeting early maturity (E1-E4, E7, E9, and E10), pod shattering (qPHD1), and growth determination (Dt1) genes. This array was optimized for routine screening of soybean diversity panel (204 accessions), subjected to the 2018-2020 survey of phenology, morphology, and yield-related traits in a potential cultivation region in Poland. High broad-sense heritability (0.84-0.88) was observed for plant height, thousand grain weight, maturity date, and the first pod height. Significant positive correlations were identified between the number of seeds and pods per plant, between these two traits and seed yield per plant as well as between flowering, maturity, plant height, and first pod height. PCR array genotyping revealed high genetic diversity, yielding 98 allelic combinations. The most remarkable correlations were identified between flowering and E7 or E1, between maturity and E4 or E7 and between plant height and Dt1 or E4. The study demonstrated high applicability of this PCR array for molecular selection of soybean towards adaptation to Central Europe, designating recessive qPHD1 and dominant Dt1, E3, and E4 alleles as major targets to align soybean growth season requirements with the length of the frost-free period, improve plant performance, and increase yield.

Several rivers that are tributaries of the Oder estuary are inhabited by Salmo trutta L, the most important of which are Ina, Gowienica, and Wołczenica. Both forms of the species, sea trout and resident brown trout, are present. All rivers are traditionally stocked with either sea trout from the neighboring Pomeranian river Rega basin or resident brown trout from various locations. To examine populations in these rivers in terms of genetic structure, genetic diversity, and origin, they were analyzed using 13 microsatellite loci. Relatedness was also assessed for fish stocked in the same year. The obtained genotypes were compared with breeding stocks used for stocking in Poland. The analyses revealed a significant genetic distance between adult individuals from Ina and Rega Rivers and fish caught during electrofishing. Strong kinship relationships were identified in the sampled areas, with high proportions of fish originating from stocking and their dominance in numbers over wild juveniles, primarily in smaller tributaries. Additionally, clear separation in the origin of stocked individuals was observed. Adult trout from Ina and Rega are genetically closer to northern brown trout lineages, providing crucial information for the management and biodiversity conservation of Polish Salmo trutta populations.

Fibrillarin is a key nucleolar S-adenosyl-L-methionine (SAM)-dependent methyltransferase, highly conserved among species in both sequence and function. It is actively involved in numerous cellular processes, particularly in the early stages of pre-ribosomal RNA processing. Although a fibrillarin orthologue has been identified in Giardia, an intestinal protozoan parasite responsible for numerous infections worldwide, its functional and structural features in this parasite remain largely unexplored. In this study, bioinformatics tools were used to analyze the sequence and structure of Giardia fibrillarin to provide insights that could aid future experimental and therapeutic investigations. Taking advantage of the protein sequence of Giardia fibrillarin, multiple bioinformatics tools were employed to estimate its domains, nuclear and nucleolar localization signals (NLS and NoLS), post-translational modifications, phylogeny, and three-dimensional structure. The analysis revealed significant conservation of Giardia fibrillarin, showing close relationships with archaeal and parasitic amoeba orthologs. It retains essential features such as the SAM-dependent methyltransferase domain, a glycine- and arginine-rich domain, and both NLS and NoLS. While the core region of the protein is structurally conserved, the N-terminal region exhibits notable divergence. The potential for inhibition of Giardia fibrillarin by SAM competitors suggests that it could be a promising target for drug development, particularly for strains resistant to current treatments.

Background: The activation of TGF-β pathway can facilitate tumorigenesis. Understanding the TGF-related genes (TRGs) in oral cancer and determining their prognostic value is of utmost importance.

Methods: The TRGs were selected to develop a prognostic model based on lasso regression. Oral cancer patients were classified into high-risk and low-risk groups based on the risk model. Subsequently, multivariate COX regression was employed to identify the prognostic marker. Additionally, the expression of SMURF2 was validated using quantitative real-time polymerase chain reaction (qRT-PCR) and the Human Protein Atlas (HPA) database. To investigate the relationship between SMURF2 expression and immune cell infiltrations, we conducted single-sample Gene Set Enrichment Analysis (ssGSEA) analyses.

Results: We identified 16 differentially expressed TRGs in oral cancer, all of which showed upregulation. From these, we selected eight TRGs as prognostic signatures. Furthermore, the high-risk group demonstrated lower infiltration levels of immune cells, immune score, and higher tumor purity. Interestingly, we also found that SMURF2 serves as an independent prognostic biomarker. SMURF2 was upregulated in oral cancer, as confirmed by public databases and qRT-PCR analysis. Importantly, our results indicate a close association between SMURF2 expression and the immune microenvironment.

Conclusion: The 8-TRG signature prognosis model that we constructed has the ability to predict the survival rate and immune activity of oral cancer patients. SMURF2 could be effective in recognizing prognosis and evaluating immune efficacy for oral cancer.

Currently, cancer stem cells (CSCs) are regarded as the most promising target for cancer therapy due to their close association with tumor resistance, invasion, and recurrence. Thus, identifying CSCs-related genes and constructing a prognostic risk model associated with CSCs may be crucial for hepatocellular carcinoma (HCC) therapy. Xena Browser was used to download gene expression profiles and clinical data, while MSigDB was used to obtain genes associated with CSCs. Firstly, the non-negative matrix factorization (NMF) algorithm was used to cluster the HCC samples based on CSCs-related genes. To evaluate the predictive performance of the risk model, the receiver operating characteristic curves (ROC) and Kaplan-Meier analysis were used. The R package "rms" was used to construct the final nomogram based on risk scores and clinical characteristics. Based on 449 CSCs-related genes, a total of 588 HCC samples from TCGA-LIHC and ICGC-LIRI_JP were classified into four molecular subtypes with marked differences in survival and mRNA stemness index (mRNAsi) between subtypes. Univariate Cox regression, multivariate Cox regression, and LASSO regression analyses were performed on a total of 1417 differentially expressed genes (DEGs) between subtypes, and a nine-gene prognostic model was constructed with TTK, ST6GALNAC4, SPP1, SGCB, MEP1A, HTRA1, CD79A, C6, and ATP2A3. In both the training and testing sets and the external validation cohort, the risk model performed well in predicting HCC patients' survival. A nomogram was constructed and had high predictive efficacy in short-term survival. In comparison with the other two prognostic models, our nine-gene signature model performed best. We constructed a nine-gene signature model to predict the survival of HCC patients, which has good predictive efficacy and stability. The model may contribute to guiding the prognostic assessment of HCC patients in clinical practice.

Earlier diagnosis of lung cancer is crucial for reducing mortality and morbidity in high-risk patients. Liquid biopsy is a critical technique for detecting the cancer earlier and tracking the treatment outcomes. However, noninvasive biomarkers are desperately needed due to the lack of therapeutic sensitivity and early-stage diagnosis. Therefore, we have utilized transcriptomic profiling of early-stage lung cancer patients to discover promising biomarkers and their associated metabolic functions. Initially, PCA highlights the diversity level of gene expression in three stages of lung cancer samples. We have identified two major clusters consisting of highly variant genes among the three stages. Further, a total of 7742, 6611, and 643 genes were identified as DGE for stages I-III respectively. Topological analysis of the protein-protein interaction network resulted in seven candidate biomarkers such as JUN, LYN, PTK2, UBC, HSP90AA1, TP53, and UBB cumulatively for the three stages of lung cancers. Gene enrichment and KEGG pathway analyses aid in the comprehension of pathway mechanisms and regulation of identified hub genes in lung cancer. Importantly, the medial survival rates up to ~ 70 months were identified for hub genes during the Kaplan-Meier survival analysis. Moreover, the hub genes displayed the significance of risk factors during gene expression analysis using TIMER2.0 analysis. Therefore, we have reason that these biomarkers may serve as a prospective targeting candidate with higher treatment efficacy in early-stage lung cancer patients.

Enterohemorrhagic Escherichia coli (EHEC) are pathogens that, only in the United States, cause more than 250,000 foodborne infections a year. Since antibiotics or other antidiarrheal agents may increase the hemolytic-uremic syndrome (HUS) development risk, currently only supportive therapy, including hydration, is used. Therefore, many methods to fight EHEC bacteria focus on their use in food processing to prevent human infection. One of the proposed anti-EHEC agents is bacteriophages, known for their bactericidal effect, host specificity, and lack of cross-resistance with antibiotics. In this review article, we provide an overview of the characteristics like source of isolation, morphology, kinetics of life cycle, and treatment potential of over 130 bacteriophages able to infect EHEC strains. Based on the reviewed literature, we conclude that bacteriophages may play a highly significant role in regulating EHEC propagation. In addition, we also point out the phage features that should be taken into account not only when using bacteriophages but also when examining their properties. This may contribute to accelerating the pace of work on the preventive use of bacteriophages, which is extremely needed in the modern world of the food industry, but also stimulate interest in phages and accelerate regulatory work that would enable the use of bacteriophages also in medicine, to fight the drug-resistant strains.

High-risk human papillomaviruses are well-established drivers of several cancer types including cervical, head and neck, penile as well as anal cancers. While the E6 and E7 viral oncoproteins have proven to be critical for malignant transformation, evidence is also beginning to emerge suggesting that both host pathways and additional viral genes may also be pivotal for malignant transformation. Here, we focus on the role of host APOBEC genes, which have an important role in molecular editing including in the response to the viral DNA and their role in HPV-driven carcinogenesis. Further, we also discuss data developed suggesting the existence of HPV-derived miRNAs in HPV + tumors and their potential role in regulating the host transcriptome. Collectively, while recent advances in these two areas have added complexity to the working model of papillomavirus-induced oncogenesis, these discoveries have also shed a light onto new areas of research that will be required to fully understand the process.