Essential Traits Research Articles

Enhanced IoMT security framework using group teaching optimized auto-encoder for intrusion detection

Providing security to Internet of Medical Things (IoMT) is significant worldwide problem for future generations its implementation to be successful. The traditional security methodologies developed for IoMT struggles with the specific issues of high false positives and lower detection rate. Therefore, the proposed work aims to develop a ground-breaking intrusion detection model, named as, Group Teaching Optimized Probabilistic Deep Auto-Encoder (GTPDA) for increasing the security of IoMT networks. Here, the data transformation and normalization processes are applied to balance the dataset’s properties. Then, an Intriguing Group Teaching Optimization (IGTO) algorithm is applied to choose the most correlated and essential traits from the normalized dataset for effective intrusion detection. Consequently, a Conditional Probabilistic Deep Auto-Encoder (CPDAE) model is used to more accurately classify the type of intrusion with system complexity. This study uses the BoT-IoT, Kaggle invasion dataset, and ToN-IoT open benchmarking datasets for evaluation and performance assessments. Among all, the proposed GTPDA with its various performance metrics presented, achieves an impressive 98.8% precision, 99% recall, 98.8% F1-score, and 99% accuracy, showing its significant performance in ensuring IoMT network security.

Investigating the Triple Code Model in numerical cognition using stereotactic electroencephalography.

The ability to conceptualize numerical quantities is an essential human trait. According to the "Triple Code Model" in numerical cognition, distinct neural substrates encode the processing of visual, auditory, and non-symbolic numerical representations. While our contemporary understanding of human number cognition has benefited greatly from advances in clinical imaging, limited studies have investigated the intracranial electrophysiological correlates of number processing. In this study, 13 subjects undergoing stereotactic electroencephalography for epilepsy participated in a number recognition task. Drawing upon postulates of the Triple Code Model, we presented subjects with numerical stimuli varying in representation type (symbolic vs. non-symbolic) and mode of stimuli delivery (visual vs. auditory). Time-frequency spectrograms were dimensionally reduced with principal component analysis and passed into a linear support vector machine classification algorithm to identify regions associated with number perception compared to inter-trial periods. Across representation formats, the highest classification accuracy was observed in the bilateral parietal lobes. Auditory (spoken and beeps) and visual (Arabic) number formats preferentially engaged the superior temporal cortices and the frontoparietal regions, respectively. The left parietal cortex was found to have the highest classification for number dots. Notably, the putamen exhibited robust classification accuracies in response to numerical stimuli. Analyses of spectral feature maps revealed that non-gamma frequency, below 30 Hz, had greater-than-chance classification value and could be potentially used to characterize format specific number representations. Taken together, our findings obtained from intracranial recordings provide further support and expand on the Triple Code Model for numerical cognition.

A Mutation-Based Data Enhancement Approach for Software Vulnerability Detection

Effective software vulnerability detection is paramount for ensuring the security of software systems. However, the presence of imbalanced data in extensive datasets often leads to overfitting on non-vulnerable code and suboptimal performance on vulnerable code. Traditional methods of collecting vulnerable data frequently fall short in capturing the complexities of real-world scenarios. This paper proposes a mutation-based data enhancement approach to tackle this challenge, with a focus on capturing essential traits of vulnerable source code. Our approach systematically extracts traits from extensive vulnerable source code and employs mutation operators to introduce high-level alterations. We evaluate the convergence of multiple mutation rounds using a diversity index to ensure consistent enhancements. By selecting the most effective mutation operators for subsequent model training, our approach achieves substantial accuracy improvements across diverse datasets and deep neural network models. This work represents the initial version of our approach, with continuous refinements underway to facilitate practical implementation and address real-world security challenges.

Exploration and Enrichment Analysis of the QTLome for Important Traits in Livestock Species

Background: Quantitative trait loci (QTL) are genomic regions that influence essential traits in livestock. Understanding QTL distribution and density across species’ genomes is crucial for animal genetics research. Objectives: This study explored the QTLome of cattle, pigs, sheep, and chickens by analyzing QTL distribution and evaluating the correlation between QTL, gene density, and chromosome size with the aim to identify QTL-enriched genomic regions. Methods: Data from 211,715 QTL (1994–2021) were retrieved from the AnimalQTLdb and analyzed using R software v4.2.1. Unique QTL annotations were identified, and redundant or inconsistent data were removed. Statistical analyses included Pearson correlations and binomial, hypergeometric, and bootstrap-based enrichment tests. Results: QTL densities per Mbp were 10 for bovine, 4 for pig, 1 for sheep, and 3 for chicken genomes. Analysis of QTL distribution across chromosomes revealed uneven patterns, with certain regions enriched for QTL. Correlation analysis revealed a strong positive relationship between QTL and gene density/chromosome size across all species (p < 0.05). Enrichment analysis identified pleiotropic regions, where QTL affect multiple traits, often aligning with known candidate and major genes. Significant QTL-enriched windows (p < 0.05) were detected, with 699 (187), 355 (68), 50 (15), and 38 (17) genomic windows for cattle, pigs, sheep, and chickens, respectively, associated with overall traits (and specific phenotypic categories). Conclusions: This study provides critical insights into QTL distribution and its correlation with gene density, offering valuable data for advancing genetic research in livestock species. The identification of QTL-enriched regions also highlights key areas for future exploration in trait improvement programs.

Identification and segregation of two closely linked major QTLs for kernel row number in advanced maize-teosinte populations.

Two closely linked novel loci, qKRN2-1 and qKRN2-2, associated with kernel row number were fine-mapped on chromosome 2, and a key candidate gene for qKRN2-1 was identified through expression analysis. Kernel row number (KRN) is a crucial factor influencing maize yield and serves as a significant target for maize breeding. The use of wild progenitor species can aid in identifying the essential traits for domestication and breeding. In this study, teosinte (MT1) served as the donor parent, the inbred maize line of Mo17 was used as the recurrent parent, we identified a major quantitative trait locus (QTL) for KRN, designated qKRN2, into two closely linked loci, qKRN2-1 and qKRN2-2. Here, fine mapping was performed to investigate two QTLs, qKRN2-1 and qKRN2-2, within a genomic range of 272kb and 775kb, respectively. This was achieved using a progeny test strategy in an advanced backcross population, with the two QTLs explaining 33.49% and 35.30% of the phenotypic variance. Molecular marker-assisted selection resulted in the development of two nearly isogenic lines (NILs), qKRN2-1 and qKRN2-2, which differed only in the segment containing the QTL. Notably, the maize (Mo17) alleles increased the KRN relative to teosinte by approximately 1.4 and 1.2 rows for qKRN2-1 and qKRN2-2, respectively. Zm00001d002989 encodes a cytokinin oxidase/dehydrogenase and its expression in the immature ears exhibited significant differences among the qKRN2-1 NILs. In situ hybridization localized Zm00001d002989 to the primordia of the inflorescence meristem and spikelet pair meristems, is predicted to be the causal gene of qKRN2-1. The findings of this study deepen our understanding of the genetic basis of KRN and hold significant potential for improving maize grain yields.

Maternally expressed OsFERTILIZATION INDEPENDENT ENDOSPERM1 regulates seed dormancy and aleurone development in rice.

Seed dormancy, an essential trait for plant adaptation, is determined by the embryo itself and the surrounding tissues. Here, we found that rice (Oryza sativa) FERTILIZATION INDEPENDENT ENDOSPERM1 (OsFIE1) regulates endosperm-imposed dormancy and the dorsal aleurone thickness in a manner dependent on the parent of origin. Maternally expressed OsFIE1 suppresses gibberellin (GA) biosynthesis in the endosperm by depositing trimethylation of lysine 27 on histone H3 (H3K27me3) marks on GA biosynthesis-related genes, thus inhibiting germination and aleurone differentiation. Knockout of rice GA 20-oxidase1 (OsGA20ox1) alleviated the phenotypic defects in osfie1. The aleurone-positive determinant Crinkly 4 (OsCR4) is another target of the OsFIE1-containing Polycomb repressive complex 2 (PRC2). We found that OsFIE1 plays an important role in genomic imprinting in the endosperm of germinating seeds, particularly for paternally expressed genes associated with H3K27me3. The increased aleurone thickness of osfie1 substantially improved grain nutritional quality, indicating that the osfie1 gene may be utilized for breeding nutrient-enriched rice. The findings provide insights into the essential roles of PRC2-mediated H3K27me3 methylation in the acquisition of seed dormancy and endosperm cell differentiation in rice.

Results of determining essential breeding traits of a standard grain sorghum sample

The selection of promising grain sorghum varieties according to the breeding results is complicated by the fact that it is necessary to take into account 49 characteristics (identifiers). This essentially multi-criteria comparison problem currently has neither a theoretical nor an unambiguous practical solution, which determines the relevance of the current study. The purpose of the study was to identify the essential characteristics (identifiers) and their scientifically based scoring of a standard grain sorghum sample based on the method of expert estimations. Based on the results of the expert estimation including leading specialists in grain sorghum breeding, there have been ranked 26 traits out of 49, provided for by the current international classifier, which can be quantitatively digitized and which also reflect biological properties, morphological descriptors of the variety, its productivity, resistance to diseases, chemical composition, etc. After conducting a ranking procedure, estimation of the representativeness of the selection, the consistency of expert opinions and the non-accidentality of their agreement, there was carried out a structuring of the totality of statistical material (rank estimation) according to the integral function of the accumulated frequencies of each ranked feature’s appearance using the original author’s computer program. As a result, there have been identified 13 significant (most significant) estimation traits of grain sorghum, amounting to 64.1 % in terms of ranking and 50 % in terms of quantitative significance. There was set up an estimation scale for them, based on their rank significance on a 100-point scale for the standard grain sorghum sample (“Zernogradskoe 88” developed by the “ARC “Donskoy”). Based on the data of determining the significance of the corresponding traits in physical terms of the compared and standard samples, as well as its score rating for the standard, there was established a point rating of the corresponding traits for the compared samples and complex estimation indicators as their sum. The complex indicator for the compared samples of the varieties ‘Ataman’ and ‘Esaul’ developed by the “ARC “Donskoy” was calculated in accordance with the share of each index relative to the standard one. Their quantitative comprehensive estimation was 111.43 and 101.93 points, respectively. Thus, these varieties exceeded the standard for a set of traits by 111.43 and 101.93 %, respectively.

On-farm evaluation of commonly grown rice cultivars from Jumla, Nepal, based on different agronomic traits

The wide distribution and diversity have been identified in agro-morphological and quantitative traits of rice grown in Jumla district which is reported as the highest altitude in the world for rice cultivation. Local landraces and improved cultivars are commonly grown by Jumla Farmers. This research explored rice cultivars planted at different altitudes under field conditions to characterize and evaluate agro-morphological traits and their correlation. Results showed, there was no significant difference in yield between local landraces and improved varieties. Influence of altitudinal variation on local landraces was scarce, while its effect on improved variety: Chandannath-1 was significant. This study suggested that local landraces such as Jumli Marshi, Daarime Marshi and Raato Marshi were not significantly different from the improved varieties and suggested cultivation of local landraces because of better price and profit. Clustering observations showed the considerable performance of Cluster 4 regarding panicle length (PL), number of grains per panicle (NGPP), and thousand grain weight (TGW) which are essential traits for higher grain yield. The correlation and path analysis showed that yield had strong positive correlations with Number of tillers per hill (NTPH) and moderate positive correlations with Flag leaf length (FLL), PL, NGPP, and Grains weight per panicle (GWPP). This study indicated that GWPP and NTPH possessed both positive correlation and high positive direct effects. Further studies are needed to evaluate the qualitative and quantitative traits of both local landraces and improved varieties to provide farmers with sound recommendations.

Dengue-mediated changes in the vectorial capacity of Aedes aegypti (Diptera: Culicidae): manipulation of transmission or infection by-product?

An arthropod's vectorial capacity summarizes its disease transmission potential. Life-history traits, such as fecundity or survival, and behavioral traits, such as locomotor activity, host-seeking and feeding behavior, are important components of vectorial capacity. Studies have shown that mosquito-borne pathogens may alter important vectorial capacity traits of their mosquito vectors, thus directly impacting their transmission and epidemic potential. Here, we compile and discuss the evidence supporting dengue-mediated changes in the yellow fever mosquito Aedes aegypti (L.), its primary vector, and evaluate whether the observed effects represent an evolved trait manipulation with epidemiological implications. Dengue infection appears to manipulate essential traits that facilitate vector-host contact, such as locomotor activity, host-seeking, and feeding behavior, but the underlying mechanisms are still not understood. Conversely, life-history traits relevant to vector population dynamics, such as survival, oviposition, and fecundity, appear to be negatively impacted by dengue virus. Overall, any detrimental effects on life-history traits may be a negligible cost derived from the virulence that dengue has evolved to facilitate its transmission by manipulating Ae. aegypti behavior and feeding performance. However, methodological disparities among studies render comparisons difficult and limit the ability to reach well-supported conclusions. This highlights the need for more standardized methods for the research into changes in virus-mediated traits. Eventually, we argue that the effects on life-history traits and behavior outlined here must be considered when assessing the epidemiological impact of dengue or other arbovirus-vector-host interactions.

A point mutation in the zinc-finger transcription factor CqLOL1 controls the green flesh color in chieh-qua (Benincasa hispida Cogn. var. Chieh-qua How).

Flesh color is an essential trait in chieh-qua (Benincasa hispida Cogn. var. Chieh-qua How); however, the inheritance and molecular basis of green flesh trait remain unclear. In the present study, two F2 populations, derived from 1742 (white flesh) × FJ3211 (green flesh) and J16 (white flesh) × FJ5 (green flesh), were used to identify the green flesh (Cqgf) locus. Genetic analysis revealed that the presence of green flesh was a quantitative trait that closely followed a normal distribution. Combining the results from QTL mapping and BSA-seq analysis, the Cqgf locus was preliminarily determined to be located on chromosome 05 and was narrowed down to a 2.55-Mb interval by linkage analysis. A large J16 × FJ5 F2 population comprising 3,180 individuals was subsequently used to screen the recombinants, and the Cqgf locus was fine-mapped to a region of 329.70 kb that harbors six genes. One of the candidate genes, Bch05G003700, the zinc-finger transcription factor LOL1 (lsd one like 1 protein; CqLOL1), was the strongest candidate gene for the Cqgf locus according to sequence variation and expression analysis. Additionally, a point mutation (A > C) in CqLOL1 resulted in the substitution of threonine (T) with proline (P) in the amino acid sequence, showing a complete relationship linked with flesh color in a panel of 45 germplasms. The study suggests that CqLOL1 promotes the accumulation of chlorophyll content in chieh-qua and lead to green flesh. Our findings establish a theoretical and technical foundation for breeding different flesh color lines and elucidating the underlying mechanisms of flesh color in chieh-qua.

The impact of resilience on academic performance with a focus on mature learners

BackgroundResilience is an essential psychological trait that empowers individuals to adapt and thrive in the face of challenges. Although it is acknowledged that health professionals need to possess high levels of resilience, there has been limited research comparing how different groups of health students, particularly school leaver undergraduates and mature age graduate entry students, develop resilience in their coursework.MethodsThis study combines both objective (academic grades with validated survey results) and subjective data (interviews) to compare how resilience is related to academic coursework performance for two groups of pharmacy students: the mature age graduate entry (GE, N = 64) learners and school leaver undergraduate (UG, N = 208) learners. We employed a sequential explanatory mixed methods design using surveys, academic performance data and semi-structured interviews. The survey tapped constructs related to resilience (burnout, stressors and coping methods) while the interviews elicited a more nuanced understanding of individual and environmental factors.ResultsAlthough there was no statistical difference in burnout experience between the two groups, GE students exhibited more positive resilience attitudes than UG when selecting resilience statements on the survey. Both cohorts indicated in the survey that engaging in distraction activities (physical exercise, sleeping, listening to music, anything other than the stressor) was their most preferred method of relieving stress. Within UG student survey responses, those who indicated support from partners, friends and family had better academic performance, while those who did not report coping methods did worse academically. The three key environmental factors we identified that contributed to both undergraduate and graduate entry resilience were workload, feedback provision and psychosocial support.ConclusionsCurrently, there is still a need for resilience programs geared at academic success to be implemented in higher education. This study provides objective evidence of academic success coupled with exploration into the nuances of resilience amongst different student groups. It not only highlights the differing resilience development strategies and burnout coping mechanisms in emerging health professionals, but showcases the juxtaposition of two different learner groups (UG and GE students) within a discipline. The cross-cohort facilitation of learning as in the discipline-specific strategies identified can help both groups develop resilience and inform future innovations. By comparing mature-age graduate students and younger-in-age undergraduate students, we identified a wider range of strategies and more positive attitudes to burnout in mature-age students. Health and clinical educators in university health degrees, clinical placements and clinical workplaces can develop effective training materials based on findings from this study to 1) assist undergraduate younger-age health students with developing resilience and 2) further refine mature-age health students’ and practicing health professionals’ resilience in today’s fast-paced clinical workplaces.

Klassisia muotoja persoonallisin kääntein: Erik Tulindbergin jousikvartetot op. 1 ja op. 2

This article concerns the String Quartets of Erik Tulindberg (1761–1814), who was the first known Finnish composer. Tulindberg was musically active primarily in the late 1770s and early 1780s, when he was studying at the Royal Academy of Turku (Kunglika Akademien i Åbo). He was respected as a skilful violinist and a chamber musician, playing in the Academy’s orchestra on ceremonial occasions and giving public concerts. Tulindberg’s compositional oeuvre comprises two Violin Concertos, six String Quartets and a few works for solo violin. The corpus of Tulindberg’s String Quartets is approached from two perspectives, namely conventional strategies of the Classical style on one hand, and Tulindberg’s recurrent choices as attributes of his personal musical language on the other. Widely used analytical tools are applied in studying the corpus, and the Quartets are compared with certain works that originate in the same period and reside in Tulindberg’s archive. The theoretical framework includes writings that focus specifically on describing the compositional strategies used in Classical and Pre-Classical music, the authors including James Hepokoski and Warren Darcy, Graham Hunt, William Caplin, Poundie Burstein and Danuta Mirka, among others. The discussion covers 1) the overall structure, the key design and cadences in the opening movements, all of which are in sonata form; 2) the essential harmonic traits; and 3) surface characteristics and expressive means such as topics, melodic figuration and instrumental writing. The analysis reveals that Tulindberg adopted the commonly used strategies and main expressive means of the Classical style. The attributes of his musical language include traits such as the constant use of extended modal mixture, enthusiasm for a varied rondo-form and frequent violoncello solos in the upper register. Although the String Quartets are conventional in structure, each one is individual in its construction. The stylistic correspondence between the works and those of composers such as Joseph Haydn, Luigi Boccherini and Ignace Pleyel, shows his thorough understanding of the music written by his contemporaries.

Codon Bias of the DDR1 Gene and Transcription Factor EHF in Multiple Species.

Milk production is an essential economic trait in cattle, and understanding the genetic regulation of this trait can enhance breeding strategies. The discoidin domain receptor 1 (DDR1) gene has been identified as a key candidate gene that influences milk production, and ETS homologous factor (EHF) is recognized as a critical transcription factor that regulates DDR1 expression. Codon usage bias, which affects gene expression and protein function, has not been fully explored in cattle. This study aims to examine the codon usage bias of DDR1 and EHF transcription factors to understand their roles in dairy production traits. Data from 24 species revealed that both DDR1 and EHF predominantly used G/C-ending codons, with the GC3 content averaging 75.49% for DDR1 and 61.72% for EHF. Synonymous codon usage analysis identified high-frequency codons for both DDR1 and EHF, with 17 codons common to both genes. Correlation analysis indicated a negative relationship between the effective number of codons and codon adaptation index for both DDR1 and EHF. Phylogenetic and clustering analyses revealed similar codon usage patterns among closely related species. These findings suggest that EHF plays a crucial role in regulating DDR1 expression, offering new insights into genetically regulating milk production in cattle.

Recurrent excision of a hAT-like transposable element in CmAPRR2 leads to the "shooting star" melon phenotype.

The external appearance of fruit commodities is an essential trait that has profound effects on consumer preferences. A natural melon variety, characterized by an uneven and patchy arrangement of dark green streaks and spots on the white-skinned rind, resembles shooting stars streaking across the sky; thus, this variety is called "Shooting Star" (SS). To investigate the mechanism underlying the SS melon rind pattern, we initially discovered that the variegated dark green color results from chlorophyll accumulation on the white skin. We then constructed a segregation population by crossing a SS inbred line with a white rind (WR) inbred line and used bulk segregant analysis (BSA) revealed that the SS phenotype is controlled by a single dominant gene, CmAPRR2, which has been previously confirmed to determine dark green coloration. Further genomic analysis revealed a hAT-like transposable element (TE) inserted in CmAPRR2. This TE in CmAPRR2 is recurrently excised from rind tissues, activating the expression of CmAPRR2. This activation promotes the accumulation of chlorophyll, leading to the variegated dark green color on the rind, and ultimately resulting in the SS rind phenotype. Therefore, we propose that the SS phenotype results from the recurrent excision of the hAT-like TE in CmAPRR2.

Exploring the wild almond, Prunus arabica (Olivier), as a genetic source for almond breeding

During the process of almond (Prunus dulcis) domestication, essential traits, which gave plants the plasticity for facing unstable environmental conditions, were lost. In general, the domestication process often narrows the natural genetic diversity. Modern selections (i.e., breeding programs) dramatically accelerated this genetic bottleneck trend to a few successful almond cultivars, which are presently the founders of most commercial cultivars worldwide. The concept of utilizing wild species as a source for important traits and for the enrichment of the gene pool was deeply discussed in previous studies. However, in almonds and other Prunus species, deliberate utilization of wild species as a genetic resource for breeding programs is quite rare. To address these significant challenges, we generated an interspecific F1 population between the Israeli almond cultivar Um el Fahem (UEF) and a specimen of a local wild almond species, Prunus arabica (P. arabica), originating from the Judea desert. This interspecific F1 population possesses high phenotypic variability, and sixteen segregating traits were phenotyped. Among the segregating traits, we were able to genetically associate six agriculturally important traits, such as leaf chlorophyll content (LCC), flower size, and fruit size. The alleles for Self-Compatibility (SC) and kernel bitterness were previously mapped in almond and were reexamined on the background of the distinctive wild genetic material of P. arabica. Finally, phenotypic interactions between traits were suggested, such as rootstock perimeter and canopy area that were positively correlated with total yield in the F1 population. This study is a first step towards developing a well-characterized almond interspecies genetic population. The availability of such a genetic tool with detailed phenotypic analysis is crucial to address and explore the profound influence of almond wild species in Prunus genetic research and breeding. By using the interspecific population as the infrastructure, we show the advantages and importance of utilizing wild relatives.

Epistatic interactions between oxytocin- and dopamine-related genes and trust.

Trust is an essential human trait. Although research suggests that the interplay between oxytocinergic and dopaminergic systems affects trust formation, little research has focused on epistatic (i.e., gene by gene) interaction effects of oxytocin- and dopamine-related genes on trust. Using a sample of 348 adults (114 men), we aimed to investigate the associations between genetic variants in oxytocin- and dopamine-related genes and the general, neighborhood, and institutional trust with consideration of sex differences. Three-way interaction between oxytocin-related gene genotypes, dopamine-related genotypes, and sex was found for the oxytocin receptor gene (OXTR)rs1042778 and the Catechol-O-Methyltransferase gene (COMT) rs4680 genotypes (p = 0.02) and for OXTR rs2254298 and the dopamine D2 receptor gene (DRD2) rs1800497 genotypes (p = 0.01). Further sex-stratified analyses revealed that the interaction between OXTR rs1042778 and COMT rs4680 genotypes was associated with neighborhood trust among men (p = 0.0007). Also, the interaction between OXTR rs2254298 and DRD2 rs1800497 genotypes was associated with institutional trust among men (p = 0.005). Post-hoc analyses found that men with OXTR rs1042778 TG/TT and COMT rs4680 GG genotypes reported higher neighborhood trust than those with GG + AG/AA (B = 13.49, SE = 4.68, p = 0.02), TG/TT + AG/AA (B = 23.00, SE = 5.99, p = 0.001), and GG + GG (B = 18.53, SE = 5.25, p = 0.003). Similarly, men with OXTR rs2254298 AG/AA and DRD2 rs1800497 CC genotypes showed higher institutional trust than those with AG/AA + TT/TC (B = 15.67, SE = 5.30, p = 0.02). We could not find any interacting associations among women. While we note that our sample size and candidate gene approach have a potential risk of chance findings, our study provides an important foundation toward further exploration of sex-specific epistatic interaction effects of oxytocin- and dopamine-related genes on trust, indicating the importance of both systems in trust formation.

Identification of novel genetic loci related to dromedary camel (Camelus dromedarius) morphometrics, biomechanics, and behavior by genome-wide association studies

In the realm of animal breeding for sustainability, domestic camels have traditionally been valued for their milk and meat production. However, key aspects such as zoometrics, biomechanics, and behavior have often been overlooked in terms of their genetic foundations. Recognizing this gap, the present study perfomed genome-wide association analyses to identify genetic markers associated with zoometrics-, biomechanics-, and behavior-related traits in dromedary camels (Camelus dromedarius). 16 and 108 genetic markers were significantly associated (q < 0.05) at genome and chromosome-wide levels of significance, respectively, with zoometrics- (width, length, and perimeter/girth), biomechanics- (acceleration, displacement, spatial position, and velocity), and behavior-related traits (general cognition, intelligence, and Intelligence Quotient (IQ)) in dromedaries. In most association loci, the nearest protein-coding genes are linkedto neurodevelopmental and sensory disorders. This suggests that genetic variations related to neural development and sensory perception play crucial roles in shaping a dromedary camel’s physical characteristics and behavior. In summary, this research advances our understanding of the genomic basis of essential traits in dromedary camels. Identifying specific genetic markers associated with zoometrics, biomechanics, and behavior provides valuable insights into camel domestication. Moreover, the links between these traits and genes related to neurodevelopmental and sensory disorders highlight the broader implications of domestication and modern selection on the health and welfare of dromedary camels. This knowledge could guide future breeding strategies, fostering a more holistic approach to camel husbandry and ensuring the sustainability of these animals in diverse agricultural contexts.

MiR827 orchestrates the regulation of SPX-MFS1 and SPX-MFS5 with the assistance of lncRNA767 to enhance phosphate starvation tolerance and maize development.

MicroRNA827 (miR827) is functionally conserved among different plant species and displays species-specific characteristics, but the mechanisms by which miR827 regulates phosphate (Pi) starvation tolerance and maize development remain elusive. We found that miR827 selectively targets the Pi transporter genes SPX-MFS1 and SPX-MFS5. miR827 overexpression improved the Pi starvation tolerance, plant architecture and grain yield and quality, whereas miR827 suppression yielded a contrasting phenotype. In addition, we identified a specific long noncoding RNA (lncRNA767) that serves as a direct target and a facilitator of miR827 and can stabilize the SPX-MFS1 and SPX-MFS5 transcripts, leading to their translation inhibition. The orchestrated regulation of SPX-MFS1 and SPX-MFS5 modulates PHR1; 1 and PHR1; 2, which are critical transcription factors in Pi signalling, and thereby affects the expression of downstream Pi starvation-induced genes. Together, these findings demonstrate that miR827, assisted by lncRNA767, enhances SPX-MFS1 and SPX-MFS5 suppression and thus exerts a significant impact on Pi homeostasis and several essential agronomic traits of maize.

Multi-environment evaluation of Clary sage (Salvia sclarea L.) selections for yield and essential oil traits under Western Himalayan conditions

Clary sage is an important aromatic herb that has a high potential for commercial cultivation under the diversified climates of the Western Himalayas. The present study was carried out to understand the performance of genotypes and their interaction with the varied environments prevalent in the Western Himalayas and to identify stable and best-performing genotypes. In the present experiment, ten superior selections were evaluated in four different environments as multi-location trials in a randomized block design with three replications during 2021 and 2022. The pooled analysis of variance revealed significant variations for genotypes, environments, and genotype × environment interaction for all the studied traits. The highest mean performance suggests that Env-1 has the most suitable conditions for clary sage cultivation. The genotypes CSIR-IHBT-SS-07 and CSIR-IHBT-SS-09 were found to be the best performers for fresh inflorescence weight (418.73 g/plant) and essential oil content (428.91 mg/Kg), respectively. The results of Eberhart and Russell’s regression-based model confirm that the genotype CSIR-IHBT-SS-07 is a stable and superior genotype for the economically important traits. Further, the gas-chromatography mass spectroscopic characterization of essential oil disclosed that CSIR-IHBT-SS-07 was unique in terms of the highest sclareol content (23.39–45.17 %) across all the test environments. Genotype + Genotype × Environment biplot analysis confirmed that all the test environments form a single mega-environment. The study is a pioneer in unraveling the stability response of clary sage in Western Himalaya and provides a strong base for the identification of superior genotypes and selection strategy for future genetic improvement programs of clary sage.

Unraveling genotypic interactions in sugar beet for enhanced yield stability and trait associations

The interaction between genotype and environment (GEI) significantly influences plant performance, crucial for breeding programs and ultimately boosting crop productivity. Alongside GEI, breeders encounter another hurdle in their quest for yield improvement, notably adverse and negative correlations among pivotal traits. This study delved into the stability of white sugar yield (WSY), root yield (RY), sugar content (SC), extraction coefficient of sugar (ECS), and the interplay among essential traits including RY, SC, alpha amino nitrogen (N), sodium (Na+), and potassium (K+) across 15 sugar beet hybrids and three control varieties. The investigation spanned two locations over two consecutive years (2022–2023), employing a randomized complete block design with four replications to comprehensively analyze these factors. The analysis of variance highlighted the significant effects of environment, genotype, and GEI at the 1% probability level. Notably, the AMMI analysis of GEI revealed the significance of the first component for WSY, RY, and SC, with the first two components proving significant for ECS. Within the linear mixed model (LMM), WSY, RY, SC, and ECS demonstrated significant effects from both genotype and GEI. In the WAASB biplot, genotypes 10, 8, 17, 6, 13, 14, 15, 7, 12, and 16 exhibited stability in WSY, while genotypes 9, 10, 6, 14, 7, 8, 13, 12, 18, and 15 displayed stability in RY. Additionally, genotypes 10, 15, 12, 13, 16, 17, 6, and 14 were stable for SC, and genotypes 8, 10, 7, 6, 13, 12, 16, 17, 15, 14, and 18 showcased stability in ECS, boasting above-average yield values. In the genotype by yield × trait (GYT) biplot, genotypes 15, 18, and 16 emerged as top performers when combining RY with SC, Na+, N, and K+, suggesting their potential for inclusion in breeding programs.