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Introduction: The balanced fatty acid profile of olive oil not only enhances its stability but also contributes to its positive effects on health, making it a valuable dietary choice. Olive oil's high content of unsaturated fatty acids and low content of saturated fatty acids contribute to its beneficial effects on cardiovascular diseases and cancer. The quantities of these fatty acids in olive oil may fluctuate due to various factors, with genotype being a crucial determinant of the oil's quality. Methods: This study investigated the genetic basis of oil quality by comparing the transcriptome of two Iranian cultivars with contrasting oil profiles: Mari, known for its high oleic acid content, and Shengeh, characterized by high linoleic acid at Jaén index four. Results and discussion: Gas chromatography confirmed a significant difference in fatty acid composition between the two cultivars. Mari exhibited significantly higher oleic acid content (78.48%) compared to Shengeh (48.05%), while linoleic acid content was significantly lower in Mari (4.76%) than in Shengeh (26.69%). Using RNA sequencing at Jaén index four, we analyzed genes involved in fatty acid biosynthesis. Differential expression analysis identified 2775 genes showing statistically significant differences between the cultivars. Investigating these genes across nine fundamental pathways involved in oil quality led to the identification of 25 effective genes. Further analysis revealed 78 transcription factors and 95 transcription binding sites involved in oil quality, with BPC6 and RGA emerging as unique factors. This research provides a comprehensive understanding of the genetic and molecular mechanisms underlying oil quality in olive cultivars. The findings have practical implications for olive breeders and producers, potentially streamlining cultivar selection processes and contributing to the production of high-quality olive oil. [ABSTRACT FROM AUTHOR]

Introduction: The balanced fatty acid profile of olive oil not only enhances its stability but also contributes to its positive effects on health, making it a valuable dietary choice. Olive oil's high content of unsaturated fatty acids and low content of saturated fatty acids contribute to its beneficial effects on cardiovascular diseases and cancer. The quantities of these fatty acids in olive oil may fluctuate due to various factors, with genotype being a crucial determinant of the oil's quality. Methods: This study investigated the genetic basis of oil quality by comparing the transcriptome of two Iranian cultivars with contrasting oil profiles: Mari, known for its high oleic acid content, and Shengeh, characterized by high linoleic acid at Jaén index four. Results and discussion: Gas chromatography confirmed a significant difference in fatty acid composition between the two cultivars. Mari exhibited significantly higher oleic acid content (78.48%) compared to Shengeh (48.05%), while linoleic acid content was significantly lower in Mari (4.76%) than in Shengeh (26.69%). Using RNA sequencing at Jaén index four, we analyzed genes involved in fatty acid biosynthesis. Differential expression analysis identified 2775 genes showing statistically significant differences between the cultivars. Investigating these genes across nine fundamental pathways involved in oil quality led to the identification of 25 effective genes. Further analysis revealed 78 transcription factors and 95 transcription binding sites involved in oil quality, with BPC6 and RGA emerging as unique factors. This research provides a comprehensive understanding of the genetic and molecular mechanisms underlying oil quality in olive cultivars. The findings have practical implications for olive breeders and producers, potentially streamlining cultivar selection processes and contributing to the production of high-quality olive oil. [ABSTRACT FROM AUTHOR]

MicroRNAs (miRNAs) are key regulators of gene expression in plants, influencing various biological processes such as oil quality and seed development. Although, our knowledge about miRNAs in olive (Olea europaea L.) is progressing, with several miRNAs being identified in previous studies, but most of these reported miRNAs have been predicted without the aid of a reference genome, primarily due to limited genome accessibility at the time. However, significant knowledge gaps still need to be improved in this area. This study addresses the complexities of miRNA detection in olive, using a high quality reference genome and a combination of genomics and machine learning-based methods. By leveraging random forest and support vector machine algorithms, we successfully identified 56 novel miRNAs in olive, surpassing the limitations of conventional homology-based methods. Our subsequent analysis revealed that some of these miRNAs are implicated in the regulation of key genes involved in oil quality. Within the context of oil biosynthesis pathways, the novel miRNA Oeu124369 regulates fatty acid biosynthesis by targeting acetyl-CoA acyltransferase 1 and palmitoyl-protein thioesterase, thereby influencing the production of acetyl-CoA and palmitic acid, respectively. These findings underscore the power of machine learning in unraveling the complex miRNA regulatory network in olive and provide a high quality miRNA resource for future research aimed at improving olive oil production by exploring the target genes of the identified miRNAs to understand their role and their biological processes. [ABSTRACT FROM AUTHOR]

Context: Development of high-yielding potato cultivars represents the most efficient and sustainable strategy to secure global food and nutrition. In the past decades, numerous quantitative trait loci (QTL) mapping studies have identified various QTLs associated with morphological traits in potato. However, the varying genetic backgrounds of germplasm and the diverse QTL analysis algorithms restrict the utility of identified QTLs for research. Aims: One of the primary objectives of breeders is to identify consistent chromosomal regions linked to economically significant quantitative traits associated with yield through QTL analysis. To achieve this, an investigation was conducted to pinpoint the most stable QTLs for traits such as maturity, harvest index, plant height, stem diameter, tuber starch content, sprouting, and flesh colour. Methods: In order to detect stable QTLs for major agronomic traits, metaQTL analysis was performed using 294 QTLs from 14 publications. Key results: A total of 10 metaQTLs were found to be associated with seven morphological traits. Meta-analysis was considerably refined as compared to the initial QTLs and provided the closest flanking markers for investigated traits and reduce confidence interval mainly to five folds as compared to the mean confidence interval of initial QTLs. The metaQTLs of morphological traits juxtaposed along Chromosomes II, III, IV, and V from independent studies were considered the most stable QTLs over different field trails and genetic background. Conclusions: Ten metaQTLs were identified that contain major consensus QTLs for various morphological traits in potato. Implications: This study will enable the integration of QTLs to create new cultivars with targeted quantitative traits, thereby accelerating breeding initiatives. For decades, potato breeding has been hindered by high diversity and genetic complexity. We identified the individual locations of genes that contribute to potato yield, by analysing data from 14 prior studies. This knowledge will accelerate breeding programmes. This article belongs to the Collection Plant breeding- and genetics-based tools for food security under changing climate. [ABSTRACT FROM AUTHOR]

Potato is considered a key component of the global food system and plays a vital role in strengthening world food security. A major constraint to potato production worldwide is the Potato Virus Y (PVY), belonging to the genus Potyvirus in the family of Potyviridae. Selective breeding of potato with resistance to PVY pathogens remains the best method to limit the impact of viral infections. Understanding the genetic diversity and population structure of potato germplasm is important for breeders to improve new cultivars for the sustainable use of genetic materials in potato breeding to PVY pathogens. While, genetic diversity improvement in modern potato breeding is facing increasingly narrow genetic basis and the decline of the genetic diversity. In this research, we performed genotyping-by-sequencing (GBS)-based diversity analysis on 10 commercial potato cultivars and weighted gene co-expression network analysis (WGCNA) to identify candidate genes related to PVY-resistance. WGCNA is a system biology technique that uses the WGCNA R software package to describe the correlation patterns between genes in multiple samples. In terms of consumption, these cultivars are a high rate among Iranian people. Using population structure analysis, the 10 cultivars were clustered into three groups based on the 118343 single nucleotide polymorphisms (SNPs) generated by GBS. Read depth ranged between 5 and 18. The average data size and Q30 of the reads were 145.98 Mb and 93.63%, respectively. Based on the WGCNA and gene expression analysis, the StDUF538, StGTF3C5, and StTMEM161A genes were associated with PVY resistance in the potato genome. Further, these three hub genes were significantly involved in defense mechanism where the StTMEM161A was involved in the regulation of alkalization apoplast, the StDUF538 was activated in the chloroplast degradation program, and the StGTF3C5 regulated the proteins increase related to defense in the PVY infected cells. In addition, in the genetic improvement programs, these hub genes can be used as genetic markers for screening commercial cultivars for PVY resistance. Our survey demonstrated that the combination of GBS-based genetic diversity germplasm analysis and WGCNA can assist breeders to select cultivars resistant to PVY as well as help design proper crossing schemes in potato breeding. [ABSTRACT FROM AUTHOR]

Improving the baking quality is a primary challenge in the wheat flour production value chain, as baking quality represents a crucial factor in determining its overall value. In the present study, we conducted a comparative RNA-Seq analysis on the high baking quality mutant “O-64.1.10” genotype and its low baking quality wild type "Omid" cultivar to recognize potential genes associated with bread quality. The cDNA libraries were constructed from immature grains that were 15 days post-anthesis, with an average of 16.24 and 18.97 million paired-end short-read sequences in the mutant and wild-type, respectively. A total number of 733 transcripts with differential expression were identified, 585 genes up-regulated and 188 genes down-regulated in the “O-64.1.10” genotype compared to the “Omid”. In addition, the families of HSF, bZIP, C2C2-Dof, B3-ARF, BES1, C3H, GRF, HB-HD-ZIP, PLATZ, MADS-MIKC, GARP-G2-like, NAC, OFP and TUB were appeared as the key transcription factors with specific expression in the “O-64.1.10” genotype. At the same time, pathways related to baking quality were identified through Kyoto Encyclopedia of Genes and Genomes. Collectively, we found that the endoplasmic network, metabolic pathways, secondary metabolite biosynthesis, hormone signaling pathway, B group vitamins, protein pathways, pathways associated with carbohydrate and fat metabolism, as well as the biosynthesis and metabolism of various amino acids, have a great deal of potential to play a significant role in the baking quality. Ultimately, the RNA-seq results were confirmed using quantitative Reverse Transcription PCR for some hub genes such as alpha-gliadin, low molecular weight glutenin subunit and terpene synthase (gibberellin) and as a resource for future study, 127 EST-SSR primers were generated using RNA-seq data. [ABSTRACT FROM AUTHOR]

Stability analysis is one of the most important steps that a breeder should use to release a new variety for a region. To identify and introduce the best sugarcane genotypes, an experiment with 26 promising Sugarcane genotypes along with four commercial varieties was planned and implemented during 2017–2019. This study aimed to determine a promising stable sugarcane genotype for the sugarcane-growing areas of Khuzestan Province in Iran. The effects of genotype × environment interactions on the sugar yield of 26 promising sugarcane genotypes and four standard varieties as controls were investigated for the new plant (P), first ratoon (R1), and second ratoon (R2) at three locations (Amir Kabir, Imam Khomeini, and Mianab) for three cropping seasons. For the final analysis every year, quantitative and qualitative characteristics were measured by sampling 10 stalks of each genotype in each replication and each experiment. A combined analysis was conducted with regard to the fixed effects of the genotype and environment and the random effect of the year. The sugar yield stability of the genotypes was evaluated based on nonparametric, ecovalence, Shukla, simultaneous selection, and AMMI statistical methods. According to the results, g 2 , g 4 , g 5 , g 7 , g 11 , g 12 , g 14 , g 16 , g 19 , g 20 , g 21 , g 23 , g 24 , g 26 , g 27 , g 28 , g 29 , and g 30 are the most stable genotypes based on statistical analyses. As these genotypes have general stability and can be cultivated in three crops, they are introduced for commercial cultivation. According to an AMMI biplot, genotype g 6 was considered to have special adaptation to the first location (Imam Khomeini), genotypes g 8 and g 15 were specifically adapted to the second location (Amir Kabir), and genotypes g 10 , g 17 , and g 22 showed special adaptation to the third location (Mianab). Therefore, these genotypes are introduced for commercial cultivation in the mentioned locations. [ABSTRACT FROM AUTHOR]

Diet and exercise are two critical factors that regulate gut microbiota, affecting weight management. The present study investigated the effect of 10 weeks of high-intensity interval training (HIIT) and a high-protein diet (HPD) on gut microbiota composition and body weight changes in obese male Wistar rats. Forty obese rats were randomly divided into five groups, including HPD, HIIT + HPD, HIIT + high-fat diet (HFD) (continuing HFD during intervention), obese control 1 (continuing HFD during intervention), obese control 2 (cutting off HFD at the beginning of the intervention and continuing standard diet), and eight non-obese Wistar rats as a non-obese control (NOC) group (standard diet). Microbial community composition and diversity analysis by sequencing 16S rRNA genes derived from the fecal samples, body weight, and Lee index were assessed. The body weight and Lee index in the NOC, HIIT + HFD, HPD, and HIIT + HPD groups were significantly lower than that in the OC1 and OC2 groups along with the lower body weight and Lee index in the HPD and HIIT + HPD groups compared with the HIIT + HFD group. Also, HFD consumption and switching from HFD to a standard diet or HPD increased gut microbiota dysbiosis. Furthermore, HIIT along with HFD increased the adverse effects of HFD on gut microbiota, while the HIIT + HPD increased microbial richness, improved gut microbiota dysbiosis, and changed rats' phenotype to lean. It appears that HFD discontinuation without doing HIIT does not improve gut microbiota dysbiosis. Also, the HIIT + HFD, HPD, and HIIT + HPD slow down HFD-induced weight gain, but HIIT + HPD is a more reliable strategy for weight management due to its beneficial effects on gut microbiota composition. [ABSTRACT FROM AUTHOR]

The study presents the genome analysis of a new Pseudomonas sp. (SWRIQ11), which can alleviate salinity stress effects on growth of olive seedlings in greenhouse study. The strain SWRIQ11 can tolerate salinity up to 6%, produce siderophores, indole acetic acid (IAA), aminocyclopropane-1-carboxylate (ACC) deaminase, and has the phosphate-solubilizing capability. The SWRIQ11 genome contained an assembly size of 6,196,390 bp with a GC content of 60.1%. According to derived indices based on whole-genome sequences for species delineation, including tetra nucleotide usage patterns (TETRA), genome-to-genome distance (GGDC), and average nucleotide identity (ANI), Pseudomonas sp. SWRIQ11 can be considered a novel species candidate. The phylogenetic analysis revealed SWRIQ11 clusters with Pseudomonas tehranensis SWRI196 in the same clade. The SWRIQ11 genome was rich in genes related to stress sensing, signaling, and response, chaperones, motility, attachments, colonization, and enzymes for degrading plant-derived carbohydrates. Furthermore, the genes for production of exopolysaccharides, osmoprotectants, phytohormones, and ACC deaminase, ion homeostasis, nutrient acquisition, and antioxidant defenses were identified in the SWRIQ11 genome. The results of genome analysis (identification of more than 825 CDSs related to plant growth-promoting and stress-alleviating traits in the SWRIQ11 genome which is more than 15% of its total CDSs) are in accordance with laboratory and greenhouse experiments assigning the Pseudomonas sp. SWRIQ11 as a halotolerant plant growth-promoting bacterium (PGPB). This research highlights the potential safe application of this new PGPB species in agriculture as a potent biofertilizer. [ABSTRACT FROM AUTHOR]

Background: Olive oil contains monounsaturated oleic acid up to 83% and phenolic compounds, making it an excellent source of fat. Due to its economic importance, the quantity and quality of olive oil should be improved in parallel with international standards. In this study, we analyzed the raw RNA-seq data with a meta-analysis approach to identify important genes and their metabolic pathways involved in olive oil quality. Results: A deep search of RNA-seq published data shed light on thirty-nine experiments associated with the olive transcriptome, four of these proved to be ideal for meta-analysis. Meta-analysis confirmed the genes identified in previous studies and released new genes, which were not identified before. According to the IDR index, the meta-analysis had good power to identify new differentially expressed genes. The key genes were investigated in the metabolic pathways and were grouped into four classes based on the biosynthetic cycle of fatty acids and factors that affect oil quality. Galactose metabolism, glycolysis pathway, pyruvate metabolism, fatty acid biosynthesis, glycerolipid metabolism, and terpenoid backbone biosynthesis were the main pathways in olive oil quality. In galactose metabolism, raffinose is a suitable source of carbon along with other available sources for carbon in fruit development. The results showed that the biosynthesis of acetyl-CoA in glycolysis and pyruvate metabolism is a stable pathway to begin the biosynthesis of fatty acids. Key genes in oleic acid production as an indicator of oil quality and critical genes that played an important role in production of triacylglycerols were identified in different developmental stages. In the minor compound, the terpenoid backbone biosynthesis was investigated and important enzymes were identified as an interconnected network that produces important precursors for the synthesis of a monoterpene, diterpene, triterpene, tetraterpene, and sesquiterpene biosynthesis. Conclusions: The results of the current investigation can produce functional data related to the quality of olive oil and would be a useful step in reducing the time of cultivar screening by developing gene specific markers in olive breeding programs, releasing also new genes that could be applied in the genome editing approach. [ABSTRACT FROM AUTHOR]

The direct simulation Monte Carlo (DSMC) method, which is a probabilistic particle-based gas kinetic simulation approach, is employed in the present work to describe the physics of rarefied gas flow in super nanoporous materials (also known as mesoporous). The simulations are performed for different material porosities ( 0.5 ≤ ϕ ≤ 0.9 ), Knudsen numbers ( 0.05 ≤ Kn ≤ 1.0 ), and thermal boundary conditions (constant wall temperature and constant wall heat flux) at an inlet-to-outlet pressure ratio of 2. The present computational model captures the structure of heat and fluid flow in porous materials with various pore morphologies under rarefied gas flow regime and is applied to evaluate hydraulic tortuosity, permeability, and skin friction factor of gas (argon) flow in super nanoporous materials. The skin friction factors and permeabilities obtained from the present DSMC simulations are compared with the theoretical and numerical models available in the literature. The results show that the ratio of apparent to intrinsic permeability, hydraulic tortuosity, and skin friction factor increase with decreasing the material porosity. The hydraulic tortuosity and skin friction factor decrease with increasing the Knudsen number, leading to an increase in the apparent permeability. The results also show that the skin friction factor and apparent permeability increase with increasing the wall heat flux at a specific Knudsen number. [ABSTRACT FROM AUTHOR]

Lilium ledebourii (Baker) Boiss is a rare species, which exhibits valuable traits. However, before its genetic diversity and evolutionary were uncovered, its wild resources were jeopardized. Moreover, some ambiguities in phylogenetic relationships of this genus remain unresolved. Therefore, obtaining the whole chloroplast sequences of L. ledebourii and its comparative analysis along with other Lilium species is crucial and pivotal to understanding the evolution of this genus as well as the genetic populations. A multi-scale genome-level analysis, especially selection pressure, was conducted. Detailed third‑generation sequencing and analysis revealed a whole chloroplast genome of 151,884 bp, with an ordinary quadripartite and protected structure comprising 37.0% GC. Overall, 113 different genes were recognized in the chloroplast genome, consisting of 30 distinct tRNA genes, four distinct ribosomal RNAs genes, and 79 unique protein-encoding genes. Here, 3234 SSRs and 2053 complex repeats were identified, and a comprehensive analysis was performed for IR expansion and contraction, and codon usage bias. Moreover, genome-wide sliding window analysis revealed the variability of rpl32-trnL-ccsA, petD-rpoA, ycf1, psbI-trnS-trnG, rps15-ycf1, trnR, trnT-trnL, and trnP-psaJ-rpl33 were higher among the 48 Lilium cp genomes, displaying higher variability of nucleotide in SC regions. Following 1128 pairwise comparisons, ndhB, psbJ, psbZ, and ycf2 exhibit zero synonymous substitution, revealing divergence or genetic restriction. Furthermore, out of 78 protein-coding genes, we found that accD and rpl36 under positive selection: however, at the entire-chloroplast protein scale, the Lilium species have gone through a purifying selection. Also, a new phylogenetic tree for Lilium was rebuilt, and we believe that the Lilium classification is clearer than before. The genetic resources provided here will aid future studies in species identification, population genetics, and Lilium conservation. [ABSTRACT FROM AUTHOR]

A high-quality transcriptome is required to advance numerous bioinformatics workflows. Nevertheless, the effectuality of tools for de novo assembly and real precision assembled transcriptomes looks somewhat unexplored, particularly for non-model organisms with complicated (very long, heterozygous, polyploid) genomes. To disclose the performance of various transcriptome assembly programs, this study built 11 single assemblies and analyzed their performance on some significant reference-free and reference-based criteria. As well as to reconfirm the outputs of benchmarks, 55 BLAST were performed and compared using 11 constructed transcriptomes. Concisely, normalized benchmarking demonstrated that Velvet–Oases suffer from the worst results, while the EvidentialGene strategy can provide the most comprehensive and accurate transcriptome of Lilium ledebourii (Baker) Boiss. The BLAST results also confirmed the superiority of EvidentialGene, so it could capture even up to 59% more (than Velvet–Oases) unique gene hits. To promote assembly optimization, with the help of normalized benchmarking, PCA and AHC, it is emphasized that each metric can only provide part of the transcriptome status, and one should never settle for just a few evaluation criteria. This study supplies a framework for benchmarking and optimizing the efficiency of assembly approaches to analyze RNA-Seq data and reveals that selecting an inefficient assembly strategy might result in less identification of unique gene hits. [ABSTRACT FROM AUTHOR]

Palaeoparasitology investigates parasitological infections in animals and humans of past distance by examining biological remains. Palaeofaeces (or coprolites) are biological remains that provide valuable information on the disease, diet, and population movements in ancient times. Today, advances in detecting ancient DNA have cast light on dark corners that microscopy could never reach. The archaeological site of the Chehrabad salt mine of Achaemenid (550–330 BC) and Sassanid (third–seventh century AD) provides remains of various biotic and abiotic samples, including animal coprolites, for multidisciplinary studies. In the present work, we investigated coprolites for helminth eggs and larvae by microscopy and traced their biological agents' DNA by Next Generation Sequencing. Our results revealed various helminths, including Taenia asiatica, the species introduced in the 1990s. Implementing advanced modern molecular techniques like NGS gives a paramount view of pathogenic agents in space and time. [ABSTRACT FROM AUTHOR]

Lilium ledebourii (Baker) Boiss is a rare species, which exhibits valuable traits. However, before its genetic diversity and evolutionary were uncovered, its wild resources were jeopardized. Moreover, some ambiguities in phylogenetic relationships of this genus remain unresolved. Therefore, obtaining the whole chloroplast sequences of L. ledebourii and its comparative analysis along with other Lilium species is crucial and pivotal to understanding the evolution of this genus as well as the genetic populations. A multi-scale genome-level analysis, especially selection pressure, was conducted. Detailed third‑generation sequencing and analysis revealed a whole chloroplast genome of 151,884 bp, with an ordinary quadripartite and protected structure comprising 37.0% GC. Overall, 113 different genes were recognized in the chloroplast genome, consisting of 30 distinct tRNA genes, four distinct ribosomal RNAs genes, and 79 unique protein-encoding genes. Here, 3234 SSRs and 2053 complex repeats were identified, and a comprehensive analysis was performed for IR expansion and contraction, and codon usage bias. Moreover, genome-wide sliding window analysis revealed the variability of rpl32-trnL-ccsA, petD-rpoA, ycf1, psbI-trnS-trnG, rps15-ycf1, trnR, trnT-trnL, and trnP-psaJ-rpl33 were higher among the 48 Lilium cp genomes, displaying higher variability of nucleotide in SC regions. Following 1128 pairwise comparisons, ndhB, psbJ, psbZ, and ycf2 exhibit zero synonymous substitution, revealing divergence or genetic restriction. Furthermore, out of 78 protein-coding genes, we found that accD and rpl36 under positive selection: however, at the entire-chloroplast protein scale, the Lilium species have gone through a purifying selection. Also, a new phylogenetic tree for Lilium was rebuilt, and we believe that the Lilium classification is clearer than before. The genetic resources provided here will aid future studies in species identification, population genetics, and Lilium conservation. [ABSTRACT FROM AUTHOR]

Lavandula genus is a considerable medicinal plant in pharmaceutical and cosmetics industries. Considering increasing threat of drought in the world, it is important to identify genotypes which can tolerate drought. It is also important to characterize quantity and quality of essential oils, and tolerance indicators of these genotypes against drought stress. Therefore, an experiment was conducted in Gorgan University of Agricultural Sciences and Natural Resources, Iran, during 2017 and 2018, to investigate these factors. It was a factorial experiment based on randomized complete block design with two treatments, three genotypes (Lavandula angustifolia cv. Hidcote, Lavandula angustifolia cv. Munstead, and Lavandula stricta), and four levels of drought stress (irrigation regimes) (I1: 100–90% (control), I2: 80–70%, I3: 60–50% and I4: 30–40% of field capacity) which was done with three repetitions. Drought increased amount of proline in leaves, antioxidant activity, activity of catalase, peroxidase, ascorbate peroxidase, and superoxide enzymes, malondialdehyde content, total flavonoids, total phenol, total sugar and essential oil percentage. The PCA analysis of different irrigation regimes showed that in the first component, the best traits are antioxidant enzymes CAT, SOD, APX, while in the second component, only the trait Catalase is the best trait. The results of PCA analysis in lavender genotypes showed that L. stricta exhibits the most affected physiological changes while trying to adjust to changes in the water status of the environment, under the imposed conditions and shows the highest resistance. But it reduced dry weight of aerial parts, relative water content of leaves, and efficacy of essential oil. Lavandula stricta genotype had the highest amount of essential oil, but the highest dry weight of the aerial parts and essential oil yield were related to L. angustifolia cv. Hidcote and L. angustifolia cv. Munstead genotypes. In all evaluated genotypes, with increasing drought stress, monoterpene compounds were decreased and sesquiterpene compounds were increased. Totally it was shown that drought effect on evaluated traits depends on genotype and nature of traits; this indicates that by choosing drought-tolerant genotypes in breeding programs, high quantity and quality of essential oil, as well as tolerance to drought stress can be achieved. [ABSTRACT FROM AUTHOR]

Plant growth and yield are affected often by stress conditions including drought, which is the most important abiotic stress to reduce crop production worldwide. Milk thistle is one of the momentous medicinal crops with high potential as a multiple-purpose plant for low-efficient cultivation systems in the arid and semiarid areas. In this experiment, the effect of Chitosan (100 and 200 mg/l) and salicylic acid (0.5 and 1 mM) was investigated on plant traits (morphological, physiological, and phytochemical) under different levels of water deficit (Field capacity (F.C), 70% F.C, 40% F.C). Data were recorded in a time course (3, 7, 14, and 21 days after stress) and subjected to statistical analyses. According to the results, morphological, physiological, and phytochemical traits of the plant were significantly affected by water deficit, elicitors, and stress durations. Comparing the stress levels showed that severe water stress (40% F.C) significantly reduced growth and yield, while mild stress (70% F.C) did not show significant difference to non-stress treatment (F.C). The results showed that both chitosan and salicylic acid elicitors increased growth and yield, stress tolerance of plants under water-deficit conditions, and promotion of flavonoids, but chitosan has a more prominent effect. Under severe stress conditions, chitosan increased the yield of fresh and dry weight by 76.4% and 72.4%, but salicylic acid increased fresh weight and dry weight by 27.1% and 58.8%, respectively. Conversely, salicylic acid resulted in a 77.8% increase in grain yield, while that of chitosan was 75.0%. On the other hand, the content of silybin A in treatments of salicylic acid and chitosan, was increased by 2.9 and 9.2 mg/g, respectively, while the content of silybin B was increased by 6.48 and 9.48 mg/g, respectively. The role of the elicitors in reducing the negative effects of water stress and plant tolerance is due to stimulation of osmoregulation through proline and soluble sugar accumulation, reduction of malondialdehyde level, and production of antioxidant enzymes. [ABSTRACT FROM AUTHOR]

Meta-QTL (MQTL) analysis is a robust approach for genetic dissection of complex quantitative traits. Rice varieties adapted to non-flooded cultivation are highly desirable in breeding programs due to the water deficit global problem. In order to identify stable QTLs for major agronomic traits under water deficit conditions, we performed a comprehensive MQTL analysis on 563 QTLs from 67 rice populations published from 2001 to 2019. Yield and yield-related traits including grain weight, heading date, plant height, tiller number as well as root architecture-related traits including root dry weight, root length, root number, root thickness, the ratio of deep rooting and plant water content under water deficit condition were investigated. A total of 61 stable MQTLs over different genetic backgrounds and environments were identified. The average confidence interval of MQTLs was considerably refined compared to the initial QTLs, resulted in the identification of some well-known functionally characterized genes and several putative novel CGs for investigated traits. Ortho-MQTL mining based on genomic collinearity between rice and maize allowed identification of five ortho-MQTLs between these two cereals. The results can help breeders to improve yield under water deficit conditions. [ABSTRACT FROM AUTHOR]

Background: Improving yield and yield-related traits is the crucial goal in breeding programmes of cereals. Meta-QTL (MQTL) analysis discovers the most stable QTLs regardless of populations genetic background and field trial conditions and effectively narrows down the confidence interval (CI) for identification of candidate genes (CG) and markers development. Results: A comprehensive MQTL analysis was implemented on 1052 QTLs reported for yield (YLD), grain weight (GW), heading date (HD), plant height (PH) and tiller number (TN) in 122 rice populations evaluated under normal condition from 1996 to 2019. Consequently, these QTLs were confined into 114 MQTLs and the average CI was reduced up to 3.5 folds in compare to the mean CI of the original QTLs with an average of 4.85 cM CI in the resulted MQTLs. Among them, 27 MQTLs with at least five initial QTLs from independent studies were considered as the most stable QTLs over different field trials and genetic backgrounds. Furthermore, several known and novel CGs were detected in the high confident MQTLs intervals. The genomic distribution of MQTLs indicated the highest density at subtelomeric chromosomal regions. Using the advantage of synteny and comparative genomics analysis, 11 and 15 ortho-MQTLs were identified at co-linear regions between rice with barley and maize, respectively. In addition, comparing resulted MQTLs with GWAS studies led to identification of eighteen common significant chromosomal regions controlling the evaluated traits. Conclusion: This comprehensive analysis defines a genome wide landscape on the most stable loci associated with reliable genetic markers and CGs for yield and yield-related traits in rice. Our findings showed that some of these information are transferable to other cereals that lead to improvement of their breeding programs. [ABSTRACT FROM AUTHOR]

Considering the complex nature of salinity tolerance mechanisms, the use of isogenic lines or mutants possessing the same genetic background albeit different tolerance to salinity is a suitable method for reduction of analytical complexity to study these mechanisms. In the present study, whole transcriptome analysis was evaluated using RNA-seq method between a salt-tolerant mutant line "M4-73-30" and its wild-type "Zarjou" cultivar at seedling stage after six hours of exposure to salt stress (300 mM NaCl). Transcriptome sequencing yielded 20 million reads for each genotype. A total number of 7116 transcripts with differential expression were identified, 1586 and 1479 of which were obtained with significantly increased expression in the mutant and the wild-type, respectively. In addition, the families of WRKY, ERF, AP2/EREBP, NAC, CTR/DRE, AP2/ERF, MAD, MIKC, HSF, and bZIP were identified as the important transcription factors with specific expression in the mutant genotype. The RNA-seq results were confirmed at several time points using qRT-PCR for some important salt-responsive genes. In general, the results revealed that the mutant accumulated higher levels of sodium ion in the root and decreased its transfer to the shoot. Also, the mutant increased the amount of potassium ion leading to the maintenance a high ratio [K+]/[Na+] in the shoot compared to its wild-type via fast stomata closure and consequently transpiration reduction under the salt stress. Moreover, a reduction in photosynthesis and respiration was observed in the mutant, resulting in utilization of the stored energy and the carbon for maintaining the plant tissues, which is considered as a mechanism of salt tolerance in plants. Up-regulation of catalase, peroxidase, and ascorbate peroxidase genes has resulted in higher accumulation of H2O2 in the wild-type compared to the mutant. Therefore, the wild-type initiated rapid ROS signals which led to less oxidative scavenging in comparison with the mutant. The mutant increased expression in the ion transporters and the channels related to the salinity to maintain the ion homeostasis. In overall, the results demonstrated that the mutant responded better to the salt stress under both osmotic and ionic stress phases and lower damage was observed in the mutant compared to its wild-type under the salt stress. [ABSTRACT FROM AUTHOR]

Trachyspermum ammi (L.) Sprague, commonly known as 'Ajowan', belongs to the family 'Apiaceae'. Ajowan fruits yield 2–6% essential oil, and thymol is the major constituent of the oil (35–60%). T. ammi is of high medicinal value; however, the genomic resources for this medicinal plant are rare. To obtain transcript sequences of ajowan inflorescence, RNA-Seq was applied using Illumina HiSeq 2000 platform. Following de novo assembly, 68051 unigenes were produced, among which 43156 unigenes were annotated against different sequence databases. Blastx results of ajowan unigenes showed that 41950 and 29273 unigenes were hit in the NCBI non-redundant (Nr) protein and UniProt databases, respectively. Gene Ontology (GO) classification showed that 29258 unigenes were categorized into 55 GO terms, and 26002 unigenes were clustered in the Orthologous Group categories. Blastx results against the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database indicated that 14986 unigenes were represented in 127 pathways. In addition, 8751 sequences containing simple sequence repeats (SSRs) and 1180 putative transcription factor genes were also identified. As far as we know, this repository of genomic information is the first resource currently available for transcriptome characterization, gene discovery, developing SSR molecular markers and future genomic research on ajowan. [ABSTRACT FROM AUTHOR]

Micronutrient deficiency is one of the most common and widespread nutritional issues. Among the factors mitigating the bioavailability of Zn (zinc) and Fe (iron), phytic acid plays a key role; therefore, in order to scrutinize genetic alterations ‎related to micronutrient and phytate contents, we examined the concentrations of zinc, iron, and phytic acid, as well as its mole ratio to ‎zinc in various wheat species grown in two planting seasons. The concentrations of phytic acid and its mole ratio to zinc were 0.61‒1.55 g kg−1dry weight and 1.88‒4.17 for autumn, and 0.97‒2.02 g kg−1dry weight and 2.10‒4.05 for spring planting. There was a significant discrepancy among wheat species; tritipyrum had the highest concentration of iron, phytic acid and its mole ratio to zinc, andT. monococcumandT. aestivumrecorded reasonable zinc bioavailability. Correlation studies between grain phytic acid concentrations and other measured traits revealed various relationships, denoting an irrefutable impact of planting season and wheat ploidy levels on modification of wheat genotypes. The characters contributing more positively with principal component (PC) 1 were Zn and Fe under spring planting and Fe under autumn planting. Spike number per square meter, biological yield and grain yield in spring cultivation, and grain zinc concentration in autumn cultivation were positively correlated to principal component (PC) 2. Given that the concentration of Fe and Zn in all the studied genotypes is relatively high and due to the existence of other desirable agronomic traits, this study believes that it could possibly enhance the applicability of some of these genotypes for breeding purposes. [ABSTRACT FROM PUBLISHER]

Two of the important traits for wheat yield are tiller and fertile tiller number, both of which have been thought to increase cereal yield in favorable and unfavorable environments. A total of 6,349 single nucleotide polymorphism (SNP) markers from the 15 K wheat Infinium array were employed for genome-wide association study (GWAS) of tillering number traits, generating a physical distance of 14,041.6 Mb based on the IWGSC wheat genome sequence. GWAS analysis using Fixed and random model Circulating Probability Unification (FarmCPU) identified a total of 47 significant marker-trait associations (MTAs) for total tiller number (TTN) and fertile tiller number (FTN) in Iranian bread wheat under different water regimes. After applying a 5% false discovery rate (FDR) threshold, a total of 13 and 11 MTAs distributed on 10 chromosomes were found to be significantly associated with TTN and FTN, respectively. Linked single nucleotide polymorphisms for IWB39005 (2A) and IWB44377 (7A) were highly significantly associated (FDR < 0.01) with TTN and FTN traits. Moreover, to validate GWAS results, meta-analysis was performed and 30 meta-QTL regions were identified on 11 chromosomes. The integration of GWAS and meta-QTLs revealed that tillering trait in wheat is a complex trait which is conditioned by the combined effects of minor changes in multiple genes. The information provided by this study can enrich the currently available candidate genes and genetic resources pools, offering evidence for subsequent analysis of genetic adaptation of wheat to different climatic conditions of Iran and other countries. [ABSTRACT FROM AUTHOR]

Mgaloblishvili, a Vitis vinifera cultivar, exhibits unique resistance traits against Plasmopara viticola, the downy mildew agent. This offers the unique opportunity of exploring the molecular responses in compatible and incompatible plant-pathogen interaction. In this study, whole transcriptomes of Mgaloblishvili, Pinot noir (a V. vinifera susceptible cultivar), and Bianca (a resistant hybrid) leaves, inoculated and non-inoculated with the pathogen, were used to identify P. viticola effector-encoding genes and plant susceptibility/resistance genes. Multiple effector-encoding genes were identified in P. viticola transcriptome, with remarkable expression differences in relation to the inoculated grapevine cultivar. Intriguingly, five apoplastic effectors specifically associated with resistance in V. vinifera. Gene coexpression network analysis identified specific modules and metabolic changes occurring during infection in the three grapevine cultivars. Analysis of these data allowed, for the first time, the detection in V. vinifera of a putative P. viticola susceptibility gene, encoding a LOB domain-containing protein. Finally, the de novo assembly of Mgaloblishvili, Pinot noir, and Bianca transcriptomes and their comparison highlighted novel candidate genes that might be at the basis of the resistant phenotype. These results open the way to functional analysis studies and to new perspectives in molecular breeding of grapevine for resistance to P. viticola. [ABSTRACT FROM AUTHOR]

The impetus of the current research is to use the direct simulation Monte Carlo (DSMC) algorithm to investigate fluid behaviour and gas transport in porous microchannels. Here, we demonstrate DSMC's capability to simulate porous media up to 40% porosity. In this study, the porous geometry is generated by a random distribution of circular obstacles through the microchannel with no interpenetration between the obstacles. The influence of the morphology along with rarefaction and gas type on the apparent permeability is investigated. Moreover, the effects of porosity, solid particle's diameter and specific surface area are considered. Our results demonstrate that although decreasing porosity intensifies tortuosity in the flow field, the tortuosity reduces at higher Knudsen numbers due to slip flow at solid boundaries. In addition, our study on two different gas species showed that the gas type affects slippage and apparent gas permeability. Finally, comparing different apparent permeability models showed that Beskok and Karniadakis model is valid only up to the early transition regime and at higher Knudsen numbers, the current data matches those models that take Knudsen diffusion into account as well. [ABSTRACT FROM AUTHOR]