A multiple marker analysis approach in the framework of the mixed-effects model was developed, allowing all markers of the entire genome to be included simultaneously in the analysis. The approach was extended to multitrait situations. The proposed method is a one-stage process, which simultaneously models the residuals and genetic effects. In addition, it can easily accommodate co-variates, extra sources of variation, fixed or random including polygenic effects and it can easily be generalized to experimental and crossing designs commonly used. The developed approach considered an unstructured co-variance model for the traits residuals and fitted a multiplicative model for the trait by marker effects. The particular multiplicative model considered herein was the factor analytic model. This provided a parsimonious model specification to limit the numberof parameters to be estimated. It was shown through the simulation study that modelling multiple phenotypes in a single linkage analysis simultaneously could markedly increase the power, compared with modelling of each phenotype separately. Correlations among phenotypes can arise from several different causal processes, which may have different implications for the power and performance of the multivariate linkage analysis. Obviously, further studies using the approach suggested herein for multitrait quantitative trait loci (QTL) mapping that specifically consider different situations, should be undertaken. Furthermore, the efficiency of the model to distinguish between a pleiotropic QTL and closely linked QTL affecting different traits is another area that needs more investigation.

Background: Rheumatoid arthritis (RA) and osteoarthritis (OA) are prevalent chronic joint disorders with immunological pathogenesis. However, the causal relationships between circulating immune cells and them remain largely unknown. Therefore, we conducted a bidirectional two-sample Mendelian randomization (MR) study to determine their causal relationship. Methods: Genome-wide association study summary statistics were extracted from publicly available databases regarding immune cell phenotypes, RA, and OA. MR analysis was conducted using five MR methods, with inverse-variance-weighted (IVW) as the primary analysis method. False discovery rate correction (FDR) was used to reduce the likelihood of type 1 errors. We also conducted MR-Egger intercept tests to evaluate horizontal pleiotropy. Results: After FDR adjustment of the P values for the IVW method, the CD27 expression on memory B cells was negatively related to the risk of RA (P < 0.001), and the human leukocyte antigen (HLA)--DR expression on CD14+ monocytes was negatively related to the risk of OA (P < 0.001). We also found that RA was negatively associated with the expression of HLA-DR on myeloid dendritic cells (P < 0.001), but significant horizontal pleiotropy was observed. Conclusion: Our study demonstrates a causal relationship between specific immune cell traits and RA as well as OA, providing further insight into the role of immune cells in the pathogenesis of these disorders.

Yield and most morphological traits are controlled by the numerous of genes. In order to QTL mapping for yield and yield components traits, 169 barley recombinant inbred lines (F6 generation) and their parents “Igre” and “Arigashar”, were planted in a simple lattice design with two replications in Ghezlagh (research farm of Abouraihan college, Tehran University in 2007. The traits evaluated including: number of speckle, 1000-seed weight and yield. Analysis of variation showed that there was sufficient variation among the entries. Among traits in this study, the 1000-grain weight with the highest heritability is controlled mainly by additive effects. AFLP and SSR markers were used for preparing linkage map and 4 chromosomes of barley were mapped. Two QTLs identified for each trait on the number of 2 and 5 linkage maps. in and 5 linkage groups. Allelic effects (additive) justified the positive and negative correlation among traits. pleiotropy of QTLs or linkage between them might lead to high correlation.

Cytokine-mediated cancer therapy has the potential to enhance immunotherapeutic approaches and cancer elimination plans through the endowing of the immune system by providing improved anticancer immunity. Despite the encouraging pioneer studies on interleukins (ILs), the influence of ILs-originated therapeutics is still restricted by a class of potent immunoregulatory cytokines, systemic dose-limiting toxicities, ILs pleiotropy, and administration issues. During previous years, the area of transferring genes encoding immunostimulatory ILs was fundamentally widened to overcome these challenges and expedite ILs-based tumor regression. Numerous viral and non-viral delivery systems are currently available to act as crucial elements of the gene therapy toolbox. Moreover, cell-based cancer therapies are recruiting MSCs in the role of versatile gene delivery platforms to design one of the promising therapeutic approaches. These formulated gene carrier systems can provide possible alternatives to diminish dose-limiting adverse effects, promote administration, and enhance the therapeutic activity of ILs-derived treatment modalities in cancer treatment. This review provides a discussion on the advances of ILs gene delivery systems while focusing on the developing platforms in preclinical cancer immunogene therapy studies.

Traits such as soluble solids content, fruit acidity, pH, fruit lycopene concentration, fruit beta-carotene concentration, and fruit xanthophyll concentration are very important to the tomato industry. In this study, quantitative trait loci (QTL) analysis of these traits was performed using a recombinant inbred line (RIL) population derived from a cross between a tomato (Lycopersiconesculentum Mill) line, NC84173, and an inbred accession, LA722 (Lycopersicon pimpinellifolium). The two parental lines and the 116 RILs were planted in an alphalattice design with two replications. At the end of the growing season, 30-50 representative ripened fruits were harvested randomly from each RIL and the parents to record the traits. A linkage map was constructed using 121RFLP and 67RGA markers arranged in 12 groups. Transgressive segregation was observed for all the traits. A total of 10 quantitative trait loci (QTLs) were detected for the six traits using composite interval mapping. Colocalization of QTLs for lycopene, beta-carotene, and xanthophyll may reflect the pleiotropy effect or genetic linkage between genes via physiological relationships among these traits. This analysis shows that the introgression of wild germplasm may improve the nutritional quality of tomatoes.

Background: Childhood intelligence is a critical developmental milestone influenced by genetic and environmental factors. The interplay between intelligence and vestibular function, which is increasingly recognized for its relevance to cognitive abilities, has not been extensively studied. This study aims to investigate the potential association between childhood intelligence and vestibular dysfunction. Methods: Utilizing a two-sample Mendelian randomization (MR) approach, we analyzed data from publicly available genome-wide association studies (GWAS) of European ancestry. Genetic instruments were selected based on GWAS significance, independence, and F-statistics. We employed MR Egger, Weighted median, Inverse variance weighted (IVW), Simple mode, and Weighted mode methods for robustness checks. Results: Our analysis identified a significant inverse association between childhood intelligence and the risk of vestibular dysfunction (IVW: OR= 0.907, 95% CI = 0.843 - 0.976, p= 0.009). The MR Egger intercept test did not indicate horizontal pleiotropy, and heterogeneity analysis suggested consistency in the results. Conclusion: The study provides preliminary evidence of a negative correlation between childhood intelligence and vestibular dysfunction risk, suggesting that higher intelligence may be associated with a lower likelihood of vestibular issues. This finding underscores the importance of vestibular function in cognitive development and offers insights for early intervention strategies.

Background: Postpartum depression (PPD) is influenced by immune factors, particularly immune cells. The causal relationship between these cells and PPD is unclear. Methods: Bidirectional two-sample Mendelian randomization (TSMR) analysis was performed to determine the causal relationship between immune cell characteristics and PPD. The main analysis method used was the inverse variance weighted (IVW) method. To ensure the robustness, heterogeneity, and horizontal pleiotropy of the results, a comprehensive sensitivity analysis was conducted. Results: Overall, 28 immune cell phenotypes were identified as causally related to the onset of PPD. Most of them were distributed in the B cell group and the Treg cell group. Further analysis revealed that 13 types of immune cells had a promoting effect on PPD, whereas 15 types of immune cells had a protective effect. In addition, the incidence of PPD was found to be causally related to CD62L on granulocyte [IVW: OR (95%): 1. 183 (1. 037 to 1. 348), P = 0. 012]. Conclusion: The study unveils the causal link between immune cells and susceptibility to postpartum depression from a genetic standpoint, providing new directions for drug development and precision medicine for PPD treatment.