جستجوی مقالات مرتبط با کلیدواژه « ای » در نشریات گروه « بیوتکنولوژی و ژنتیک گیاهی »

The most valuable products obtained from the (Peganum harmala L.) are phenolic compounds and other biochemical contents, which widely is used in treating of many diseases. This study has been done with the goal of evaluating the effect of different habitats on some biochemical and physiological parameters in pecan plant. First, the samples were identified and collected simultaneously in the four studied habitats. A factorial experiment with a completely randomized design with three replications was conducted in the central laboratory of Razi University in 2023. Results of the analysis of the variance of the studied traits has been showed, that there is a significant difference between the ecotypes and also the two leaf and seed samples in the characteristics of total chlorophyll content, soluble sugar, flavonoid and anthocyanin. The results showed that, there is a significant difference between the ecotype and the sample in chlorophyll b index. The difference between the samples is due to the type of ecotype and the effect of the environment. There is a significant positive correlation between chlorophyll a, chlorophyll b and total chlorophyll. Phenol and flavonoid content showed significant negative correlation with total chlorophyll and positive and significant correlation with anthocyanin. Considering the content of biochemical compounds and the high content of phenols and flavonoids as antioxidant compounds in the studied samples, it can be stated that Ecotype No. 2 can be introduced to researchers as a suitable sample for further studies in the pharmaceutical field. The authors are grateful for the cooperation of the director of the Faculty of Engineering Sciences and Natural Resources, Razi University.

Plants with special compounds in their root exudates can strengthen a specific microbial community in the rhizosphere and prevent harmful microbial community from forming. The rhizosphere is a dynamic region around the plant root that is governed by the interaction between the plant and microorganisms. Plant root secretions can be influenced by plant species, plant growth stages and stress conditions and can be different; therefore, each microbial strain can regulate the expression of its genes at each stage of plant growth. Microbes are an unknown and huge source of secondary metabolites that play a very important role in the field of medicine and other industries. The present review focuses on factors inducing the production of new secondary metabolites from rhizosphere microbes. Each microbial strain has the potential to produce several compounds, but considering that the production of secondary metabolites is very costly for the cell, their synthesis is highly controlled by the cell. Studies have shown that changing the growth conditions of microbes, such as: temperature, salinity, co-cultivation (bacteria-bacteria, fungi-fungi, bacteria-fungi), change in oxygen concentration, aeration speed, addition of soil elements and rare metal ions, light radiation and also genetic engineering methods such as: insertion of strong inducible promoters, ribosome engineering, chromatin rearrangement, overexpression of pathway-specific regulatory genes and small molecules and chemical stimuli can help to discover new compounds. In this study, the above cases are explained in detail.

Machine learning plays a crucial role in identifying specific stressors that impact plant species and provides a comprehensive understanding of the challenges plants face in natural environments. The use of machine learning algorithms has significantly enhanced our ability to classify and differentiate the types of stress. There are two main methodologies in machine learning: supervised learning and unsupervised learning. In supervised learning, the model is trained using input-output data pairs, while unsupervised learning involves training the model without access to output labels. Unsupervised learning is primarily used for data exploration and dimension reduction. This detailed classification helps us better understand the distinct characteristics associated with different stressors and provides a more nuanced view of the plant stress landscape. Machine learning also enables the quantitative assessment of stress intensity and extent, allowing for an accurate evaluation of its impact on plant health and productivity. This quantitative approach helps researchers measure the true extent of stressors and their effects on the overall health of plant ecosystems. By employing advanced algorithms, machine learning can make predictions about future occurrences of stress and their potential consequences on plant ecosystems. This foresight strengthens preventive measures for sustainable agricultural practices, as researchers and practitioners can anticipate and mitigate potential threats to plant health. The purpose of this review is to provide a comprehensive understanding of the applications and concepts of machine learning in uncovering the complexity of plant stress phenotyping and elucidating the involved molecular mechanisms.

Identifying the strains carrying acquired tetracycline resistance genes is one of the important points in evaluating the safety of probiotic strains. The aim of the present study is to comprehensively evaluate tetracycline resistance in lactobacillus spp. isolated from the digestive system of Iranian backyard chickens.

In the present study, the phenotypic sensitivity patterns of 36 lactobacillus isolates belonging to four species L. reuteri, L. salivarius, L. crispatus and L. johnsonii were evaluated by measuring the Minimum Inhibitory Concentration (MIC) to tetracycline. After that, four tetracycline resistance genes tet(L), tet(M), tet(W) and tet(O) were detected in isolates with phenotypic resistance to this antibiotic based on the polymerase chain reaction method.

As a result, four isolates of L. reuteri, three isolates of L.salivarius, two isolates of L. crispatus and four isolates of L. johnsonii among the studied lactobacillus spp. showed phenotypic resistance to tetracycline. After the detection of tetracycline resistance genes in isolates with phenotypic resistance, the presence of tet(W) gene was confirmed in all investigated isolates. The simultaneous presence of tet(M), tet(L) and tet(W) genes was observed in three studied L. salivarius isolates. It was also found that the phenotypic resistance observed in three isolates of L. johnsoniiABRIG7, L. johnsoniiABRIG14 and L. johnsoniiABRIG24 is caused by the simultaneous presence of tet(O) and tet(W) genes.

This study showed that tetracycline resistance among Lactobacilli isolated from digestive system of Iranian backyard Chickens is due to the presence of single or multiple resistance genes.. We also found that tet(W) is the most widespread tetracycline resistance gene among investigated Lactobacillus isolates. Therefore, local poultry breeders should refrain from arbitrarily using tetracycline, and when the digestive system of domestic chickens is the source for probiotic microorganism selection, the evaluation of resistance to tetracycline from the phenotypic and molecular point of view should be taken into consideration in order to select safe strains.

Moringa oleifera L. belongs to the Moringaceae family and is known for its important medicinal chemicals, including flavonoids, coumarins, quinones, phenolic compounds, and alkaloids. This study focused on determining the best conditions for producing callus tissue from Moringa leaf explants and analyzing the biochemical compounds in the resulting calluses.

Leaf explants of the Moringa plant were cultured on the MS medium with various plant growth regulators (Kin or BAP at 0, 0.1, and 0.5 mg/L) either alone or in combination with 2,4-D, NAA, or IBA (each at 0, 0.5, 1, 2, and 4 mg/L). The percentage of callus production, root, and shoot formation, as well as the biochemical compounds (total flavonoid and anthocyanin contents) of the resulting calli, were recorded after 4 weeks.

This research revealed a significant difference between most hormonal treatments and the control treatment regarding the percentage of callus tissue production, roots, and shoots derived from callus tissue, as well as the fresh weight of the collected callus. The most effective hormonal treatment for callus tissue production (100%) was observed with the MS medium supplemented with 2 mg/L 2,4-D and 0.5 mg/L BAP. Also, the highest percentage of root production from callus tissue (100%) was associated with MS medium containing 2 or 4 mg/L NAA and 0.5 mg/L BAP. The MS medium supplemented with 1 mg/L NAA and 0.5 mg/L BAP exhibited the highest percentage (30.53%) of shoot production from M. oleifera callus. Furthermore, there was a significant difference among various treatments in terms of the biochemical compound contents of the resulting callus.

Based on the findings, the use of plant hormones had a positive impact on callus tissue production, as well as root and shoot production, and the biochemical characteristics of the Moringa plant. The maximum fresh weight of the callus was attained by utilizing BAP and 2-4-D in the MS medium. Enhancing the amount of flavonoid and anthocyanin in plant callus is crucial to boost the antioxidant and anticancer properties. In this study, the highest levels of biochemical compounds, particularly total flavonoid and anthocyanin content in the in vitro culture of M. oleifera L., were associated with increased concentrations of Auxin and Cytokinin.

Mastitis, a significant infectious ailment affecting dairy cows during both dry and lactation periods, has substantial impacts on animal health, economic profitability, and the dairy industry each year. This study seeks to utilize bioinformatics analysis not only to identify hub genes and biological pathways linked to mastitis in dairy cows but also to gain a deeper understanding of its implications.

21 microarray data samples were obtained from the GEO database (accession number GSE24217), comprising 9 healthy cow tissue samples and 12 E. coli infected tissue samples. These samples were assessed using GEO2R. Differentially expressed genes were identified based on two criteria: adjP-value > 0.05 and |LogFC| ≥ 1. Hub genes were identified using the CytoHubba plugin in Cytoscape software and topological analysis methods (DMNC, MCC, MNC, DEGREE). Signaling pathways were identified using the STRING tool based on an FDR > 0.05 index.

Out of 631 differentially expressed genes, 136 had low expression, and 495 had high expression in infected breast tissue compared to healthy ones. Among these, 205 genes were co-expressed in the network. 12 hub genes, including CCL19, ALB, GAPDH, PTPRC, ICAM1, IL6, IL1B, IL18, CXCL8, CCL20, CXCL16, and CCL3, were identified. The analysis of biological pathways revealed that the studied genes are involved in 66 biological pathways, with NOD-like receptor signaling pathway, TNF signaling pathway, and IL-17 signaling pathway playing important functional roles in dairy cow mastitis disease.

The discovered genes and pathways have the potential to enhance our knowledge of the complex molecular mechanisms involved in mastitis development. These discoveries could shape a thorough reform initiative focused on preventing, diagnosing, and treating mastitis. These insights are expected to pave the way for the creation of precise and dependable biomarkers for early detection and prevention of bovine E. coli mastitis, ultimately facilitating personalized treatment approaches.

This study was conducted for investigating the effect of drought different levels on morphological and physiological traits of Canola and investigating relative expression of antioxidant genes to identify the antioxidant response of tolerant genotype at drought different levels. The factorial experiment based on unbalanced completely random design was conducted at the end of the 5-leaf stage of Canola in 3 replications in the greenhouse of Agricultural Sciences Faculty of Gilan University on the year 2022. The effect of different drought levels, including non-stress (100%), low (75%), medium (50%), severe (25%) and very severe stress (20%FC) on morphological and physiological traits in SLM046 and Licord Canola genotypes, as well as the relative expression of important antioxidant genes of Ferredoxin-NADP+oxidoreductase (FNR) and NADPH-thioredoxin reductase (NTR) in the tolerant genotype were investigated using Real-time PCR based on Livak method. The interaction effect of stress on genotype for root length, shoot and root dry weight, allometric coefficient, root water weight, chlorophyll a and b, total chlorophyll, carotenoid and anthocyanin was significant at 1% probability level. The allometric coefficient at 20%FC, and root dry weight at all levels were higher in SLM046 than Licord under drought stress. Drought stress caused a decrease in RWC at 75% FC in both genotypes. Also, the drough treatment at the level of 20% FC caused a decrease in the leaf area and the treatment of all stress levels caused a decrease in the amount of anthocyanin in both genotypes. The stress treatment at 20%FC increased the amount of chlorophyll b and total chlorophyll in SLM046 genotype. The treatment at all stress levels decreased the chlorophyll a and b, total chlorophyll and carotenoid in Licord genotype. The results showed that the expression of FNR and NTR genes increased in SLM046 genotype at higher stress levels. It seems that the SLM046 is tolerant under severe and very severe drought. The increase in FNR expression, which leads to the production of NADPH, is regulated by the NTR expression, and by regulating the expression of genes involved in oxidative stress, it can cause drought tolerance and plant survival in tolerant genotype.

Aegilops species possessing the U genome are the most widely distributed species in the world. Considering the limitation in the genetic diversity in cultivated wheat, the use of wild relatives and other species of Aegilops can be provided a rich and diverse gene pool of new and ideal alleles for breeders. Therefore, the main goals of the present study were investigation of genetic diversity and population structure in Aegilops accessions collected from different regions of Iran using the CBDP markers.

In this study, the genetic diversity among 77 Aegilops accessions collected from 18 provinces in Iran and belonging to five species including Ae. biuncialis (UUMM genome), Ae. columnaris (UUMM genome) Ae. Neglecta (UUMM genome), Ae. triuncialis (UUCC genome), Ae. umbellulata (UU genome) , was evaluated using 15 CBDP primers. The obtained molecular data were subjected to statistical analyses using GenAlEx ver. 6.502, DARwin ver. 6, and Structure ver. 2.3.4 softwares.

A total of 189 polymorphic fragments were amplified using 15 used CBDP primers (95.27%). The PIC index ranged from 0.28 (CBDP15) to 0.42 (CBDP-2 CBDP-4) with an average of 0.35. The results of analysis of molecular variance (AMOVA) revealed that the highest proportion of genetic variance referred to within species (76%). Among all species, Ae. triuncialis showed the highest values of genetic parameters. The highest level of genetic similarity was found between Ae. biuncialis with Ae. columnaris (0.905) and Ae.biuncialis with Ae. neglecta (0.879). Although cluster analysis based on CBDP data classified all accessions into three main groups the grouping pattern was exactly in accordance with the genomic constitution of species. Moreover, the clustering pattern was confirmed by a principal coordinate’s analysis (PCoA). The population structure analysis further confirmed the results obtained from the cluster analysis and PCoA, so all studied accessions were grouped based on their genomic structure, degree of genetic similarity, and geographic similarities.

Results of the present study showed a high usefulness of CBDP markers in evaluating the genetic diversity in the Aegilops germplasm. Therefore, it seems that this marker technique can be used in programs related to the preparation of genetic maps and molecular phylogenetic studies. Also, the existence of high genetic diversity among some Iranian Aegilops species can provides a significant prospect for breeders to use them in pre-breeding programs in wheat.

Potato Virus Y is one of the most important damaging and limiting factors of potato cultivation. Plants cope with harmful conditions by regulating the expressions of genes at different levels including transcription, post-transcription and translation, using stress tolerance or resistance mechanisms. Therefore, regulatory factors play a very important role in gene expression regulation under stress conditions. Long non-coding RNAs are one of the most important regulatory elements of genes. The present study was conducted with the aim of identifying lncRNAs and investigation of their expression changes in PVY infected potato plants.

In this research CLC Genimic Workbench software was used for data analysis. After identifying lncRNAs, the genes affected by them were also analyzed. Then, Gene Ontology enrichment and KEGG pathway analysis were performed using STRING analysis and finally, the interactions between the identified lncRNAs and potato miRNAs were investigated.

According to the obtained results, a total of 3742 sequences were identified as novel lncRNAs in PVY infected potato transcriptome, of which 769 were differentially expressed. So that 310 lncRNAs were down-regulated and 459 were up-regulated in potato in response to PVY infection. Gene Ontology analysis of co-expressed genes with identified lncRNAs show the vital role of these genes in various biological processes, biosynthesis of cellular components, protein complex formation and signal transduction. Also, genes involved in biological processes related to creating defense response against stress, hypersensitive reaction, trehalose metabolism, antiviral responses related to RNA silencing and signaling pathways to induce systemic resistance, were co-expressed with identified lncRNAs in this study. The results of co-expression network between lncRNAs and miRNAs showed interactions between 56 lncRNAs and 5 miRNAs. The most interaction was observed between lncRNAs with stumiR6024-3p.

Considering the interactions between examined lncRNAs and the genes involved in defense responses against stress, it is concluded that the expression changes of these lncRNAs are an important part of the response mechanism to viral disease. The obtained results can be a step towards a better understanding of lncRNAs and their function in the development of PVY tolerance and resistance cultivars.

Data generation in biology and biotechnology has greatly increased in recent years due to the very rapid development of high-performance technologies. These data are obtained by studying biological molecules, such as metabolites, proteins, RNA, and DNA, to understand the role of these molecules in determining the structure, function, and dynamics of living systems. Functional genomics is a field of research that aims to characterize the function and interaction of all the major components (DNA, RNA, proteins, and metabolites, along with their modifications) that contribute to the set of observable characteristics of a cell or individual (i.e., phenotype). Furthermore, in a breeding program, genetic improvement can be maximized through accurate identification of superior animals that are selected as parents of the next generation, thereby achieving breeding goals. Artificial neural networks have been proposed to alleviate this limitation of traditional regression methods and can be used to handle nonlinear and complex data, even when the data is imprecise and noisy. Omics data can be too large and complex to handle through visual analysis or statistical correlations. This has encouraged the use of machine intelligence or artificial intelligence. The objectives of this study was to review the main applications of artificial intelligence methods in functional genomics, cancer, agriculture, domestic animals and its intertwined fields, i.e. epigenomics, transcriptomics, epitranscriptomics, proteomics and metabolomics, discuss important aspects of data management, such as data integration, , cleaning, noise removal, balancing and ratio of missing data, functional genomics-system modeling, artificial intelligence and systems biology, addressing legal, ethical and economic issues related to the application of artificial intelligence methods in the field of genomics and presenting a view of possible scenarios in the future.

In this review, all the researches conducted in the field of artificial intelligence application in functional genomics, cancer, agriculture, domestic animals and its intertwined fields, i.e. epigenomics, transcriptomics, epitranscriptomics, proteomics and metabolomics, were tried, focusing on the applications of recent years after Increase production of big data to be studied and used.

The studies showed that the application of artificial intelligence in all fields, including functional genomics, cancer, agriculture, domestic animals and its intertwined fields, i.e., epigenomics, transcriptomics, epitranscriptomics, proteomics, and metabolomics, is increasing rapidly and has many benefits.

Ginger (Zingiber officinale Roscoe) belongs to the Zingiberaceae family and it is one of the most important spices in the world which produces spicy and fragrant flavors and it has many healing properties. This plant does not have the ability to produce seeds due to sterility. The growth of the plant through the rhizome causes the cost of cultivation and the probability of pathogen attack. Therefore, propagation using in vitro tissue culture be effective method for increasing the rate of proliferation and infection control. For obtaining the better results in tissue culture, explants should be prepared from healthy, fresh and strong maternal sources. Somatic embryogenesis usually not used for propagation due to mutation, so it is better to use the rhizome buds as explant to preserve genetic characteristics.

For micropropagation, explants including shoot, leaf, collar and buds of ginger in were used and cultured on MS basal medium supplemented with 9 different hormonal combinations (BAP alone or in combination with NAA) for shoot induction. Shoots were transferred to MS medium containing 1 mg/l NAA or IBA for rooting. Plantlets were transferred to pots and gradually adapted to the greenhouse condition.

The best explant for fast and easy multiplication of ginger was the healthy rhizome. MS culture medium supplemented with 2 mg/l BAP and 1 mg/l NAA produced 7 shoots in each rhizome bud. The best treatment for rooting was MS medium containing 1 mg/l NAA which produced 7 roots per shoot. Then, the plantlets were successfully adopted in pots containing garden soil and cocopeat at greenhouse condition.

The results of this study showed that micropropagation of ginger plant is affected by the type of growth regulators and their concentration in MS medium and the rhizome buds were the best explants for direct in vitro propagation of ginger.

The objective of this investigation was to compare the relative expression level of the IRAK1 and TRAF6 genes in the mammary tissue of cows afflicted with clinical mastitis and unaffected cows utilizing the Real-time PCR technique. For this particular purpose, a total of 15 mammary tissue samples, consisting of 5 healthy specimens and 10 samples with clinical mastitis. An RNA extraction kit was employed to extract RNA from the designated samples. Following the assessment of both the quality and quantity of the extracted RNA, it was utilized for cDNA synthesis. Subsequently, a pair of specific primers were employed twice to ascertain the relative expression level of the desired genes in relation to the I8SrRNA gene serving as an internal control through the qPCR technique. The relative expression level of the genes was determined using the 2-ΔΔct method, while the statistical discrepancy between the diseased and healthy groups was analyzed utilizing the t-student test in SAS statistical software version 9/1. The acquired outcomes indicated that the expression levels of the TRAF6 and IRAK1 genes in the diseased samples were 2.53 (P<0.024) and 3.04 (P<0.0012) times higher, respectively. The identification of solutions to develop strategies for the control of mastitis disease is of considerable significance, with the treatment thereof possessing substantial economic rationale for the global dairy cattle industry. The results obtained from this investigation may be employed to enhance comprehension pertaining to the role of TRAF6 and IRAK1 genes within the defense system of mammary glands, as well as to devise novel examinations geared towards the identification of polymorphisms within these genes for application in breeding programs aimed at identifying mastitis-resistant animals.

Agilops is one of the most important genetic ancestors of wheat, which is a valuable genetic resource for wheat breeders due to its tolerance to various biotic and abiotic stresses. The main goal of this research was to evaluate the genetic diversity in 89 Aegilops tauschii accessions collected from different regions of Iran and the countries of Turkey, Afghanistan, Armenia, Sweden and Azerbaijan using 32 microsatellite primer pairs. The averages of polymorphic information content (PIC), Marker index (MI), Resolution (RP) indices were equal to 0.81, 1.82 and 1.88, respectively, which indicated that the primers used are suitable with high efficiency for investigating relationships among the accessions of this species. The results of principal coordinate analysis (PCoA) showed that the first three components explained 41.88% of the total genetic variance changes. Cluster analysis classified the evaluated accessions into four main groups, which was confirmed by the results of principal coordinate analysis (PCoA). According to the cluster grouping pattern, in some cases the accessions with the same geographical origin were placed in separate groups and also the presence of non-Iranian accessions in the group of Iranian accessions was observed. The results of population structure analysis confirmed the populations genetic exchanges and showed that the classification of the studied accessions is independent of their geographical origin. In general, the results showed high genetic diversity among the studied accessions of Ae. tauschii, therefore, the high genetic diversity leads to finding new allelic sources and introducing desirable alleles, which will be of great value to wheat breeders for use in breeding programs.

Leaf rust, caused by the pathogenic biotrophic fungus Puccinia triticina (Pt), is one of the most destructive wheat diseases worldwide and its negative impact on crop yields is exacerbated by higher temperatures due to climate change. Ascarosides are nematode pheromones with resistance-inducing activities against microbial pathogens and pests in various crops. We investigated the effect of ascaroside ascr#18, the major ascaroside of plant-parasitic nematodes, on infection of cv. Boolani wheat (Triticum aestivum L.) with the virulent Pt race PKTTS. After spraying with ascr#18 in the micromolar concentration range 24 hours before inoculation with fungal uredospores, the number of rust pustules on ascr#18-treated wheat leaves was greatly reduced, by 55 to over 80%, showing that ascr#18 can induce resistance in wheat to Pt. Pretreatment with ascr#18 also further enhanced the expression of defense marker genes PAL and Chitinase 3 in response to Pt as compared with untreated Pt-infected plants. Our results are consistent with and further extend previous reports that ascr#18 triggers plant immunity and primes plant for protection against pathogens. Given its broad protective effects at very low concentrations as compared to chemical resistance inducer, such as salicylic acid mimics, argue that it is an interesting tool for strengthening environmentally friendly, sustainable plant production.