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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]

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]

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]

Background: The intriguing area of paleopathology merges the disciplines of archeology and biological studies. Using this line of research, it is possible to identify diseases that have left skeletal traces in the past. In addition, diseases such as various anemia that occur in childhood, when bone tissue is soft and retains evidence, can be identified in ancient bones. Cribra orbitalia (Co ) , cribra cranii (Cc ) , and porotic hyperostosis (Ph ) were ancient skeletal remains' most common degenerative anomalies., Methods: Shahr-i Sokhta dated back to 3200-1800 BCE, is the subject of our research; it is located in Sistan and Baluchistan province (Iran). The research was done on the archaeological data collected during the MAIPS expeditions at Shahr-i Sokhta (2017-2021) kept at the storage of the excavated materials on the site. The skeletal remains were examined for bone abnormalities such as Co, Cc, and Ph. These symptoms were analyzed to obtain traces of anemia-related diseases at this site. Data has been utilized following the Data Collection Codebook., Results: Ninety-six adults were studied while the anemic signs of CC and Co are respectively seen in 27/72 (37.5 %) and 10/57 (17; 5 %), and these samples have been kept for future analysis., Conclusion: Bones may narrate a person's life, their gender and how old they were when they died besides the diseases they had. Some of the skeletons show signs of anemia, Classical paleopathology lets us to re-confirm studying diseases by further targeted sampling using molecular methods., (Copyright© 2024 Bizhani et al. Published by Tehran University of Medical Sciences.)