Huichun Xu

Melon is an important fruit crop of the Cucurbitaceae family that is being cultivated over a large area in China. Unfortunately, salt stress has crucial effects on crop plants and damages photosynthesis, membranal lipid components, and hormonal metabolism, which leads to metabolic imbalance and retarded growth. Herein, we performed RNA-seq analysis and a physiological parameter evaluation to assess the salt-induced stress impact on photosynthesis and root development activity in melon. The endogenous quantification analysis showed that the significant oxidative damage in the membranal system resulted in an increased ratio of non-bilayer/bilayer lipid (MGDG/DGDG), suggesting severe irregular stability in the photosynthetic membrane. Meanwhile, root development was slowed down by a superoxidized membrane system, and downregulated genes showed significant contributions to cell wall biosynthesis and IAA metabolism. The comparative transcriptomic analysis also exhibited that major DEGs were more common in the intrinsic membrane component, photosynthesis, and metabolism. These are all processes that are usually involved in negative responses. Further, the WGCN analysis revealed the involvement of two main network modules: the thylakoid membrane and proteins related to photosystem II. The qRT-PCR analysis exhibited that two key genes (MELO3C006053.2 and MELO3C023596.2) had significant variations in expression profiling at different time intervals of salt stress treatments (0, 6, 12, 24, and 48 h), which were also consistent with the RNA-seq results, denoting the significant accuracy of molecular dataset analysis. In summary, we performed an extensive molecular and metabolic investigation to check the salt-stress-induced physiological changes in melon and proposed that the PSII reaction centre may likely be the primary stress target.

Melon (Cucumis melo L.) is a valuable horticultural crop of the Cucurbitaceae family. Downy mildew (DM), caused by Pseudoperonospora cubensis, is a significant inhibitor of the production and quality of melon. Brassinolide (BR) is a new type of phytohormone widely used in cultivation for its broad spectrum of resistance- and defense-mechanism-improving activity. In this study, we applied various exogenous treatments (0.5, 1.0, and 2.0 mg·L−1) of BR at four distinct time periods (6 h, 12 h, 24 h, and 48 h) and explored the impact of BR on physiological indices and the genetic regulation of melon seedling leaves infected by downy-mildew-induced stress. It was mainly observed that a 2.0 mg·L−1 BR concentration effectively promoted the enhanced photosynthetic activity of seedling leaves, and quantitative real-time polymerase chain reaction (qRT-PCR) analysis similarly exhibited an upregulated expression of the predicted regulatory genes of photosystem II (PSII) CmHCF136 (MELO3C023596.2) and CmPsbY (MELO3C010708.2), thus indicating the stability of the PSII reaction center. Furthermore, 2.0 mg·L−1 BR resulted in more photosynthetic pigments (nearly three times more than the chlorophyll contents (264.52%)) as compared to the control and other treatment groups and similarly upregulated the expression trend of the predicted key enzyme genes CmLHCP (MELO3C004214.2) and CmCHLP (MELO3C017176.2) involved in chlorophyll biosynthesis. Meanwhile, the maximum contents of soluble sugars and starch (186.95% and 164.28%) were also maintained, which were similarly triggered by the upregulated expression of the predicted genes CmGlgC (MELO3C006552.2), CmSPS (MELO3C020357.2), and CmPEPC (MELO3C018724.2), thereby maintaining osmotic adjustment and efficiency in eliminating reactive oxygen species. Overall, the exogenous 2.0 mg·L−1 BR exhibited maintained antioxidant activities, plastid membranal stability, and malondialdehyde (MDA) content. The chlorophyll fluorescence parameter values of F0 (42.23%) and Fv/Fm (36.67%) were also noticed to be higher; however, nearly three times higher levels of NPQ (375.86%) and Y (NPQ) (287.10%) were observed at 48 h of treatment as compared to all other group treatments. Increased Rubisco activity was also observed (62.89%), which suggested a significant role for elevated carbon fixation and assimilation and the upregulated expression of regulatory genes linked with Rubisco activity and the PSII reaction process. In short, we deduced that the 2.0 mg·L−1 BR application has an enhancing effect on the genetic modulation of physiological indices of melon plants against downy mildew disease stress.

Abstract Background Previous work has shown a role of CCL2, a key chemokine governing monocyte trafficking, in atherosclerosis. However, it remains unknown whether targeting CCR2, the cognate receptor of CCL2, provides protection against human atherosclerotic cardiovascular disease. Methods Computationally predicted damaging or loss-of-function (REVEL > 0.5) variants within CCR2 were detected in whole-exome-sequencing data from 454,775 UK Biobank participants and tested for association with cardiovascular endpoints in gene-burden tests. Given the key role of CCR2 in monocyte mobilization, variants associated with lower monocyte count were prioritized for experimental validation. The response to CCL2 of human cells transfected with these variants was tested in migration and cAMP assays. Validated damaging variants were tested for association with cardiovascular endpoints, atherosclerosis burden, and vascular risk factors. Significant associations were replicated in six independent datasets ( n = 1,062,595). Results Carriers of 45 predicted damaging or loss-of-function CCR2 variants ( n = 787 individuals) were at lower risk of myocardial infarction and coronary artery disease. One of these variants (M249K, n = 585, 0.15% of European ancestry individuals) was associated with lower monocyte count and with both decreased downstream signaling and chemoattraction in response to CCL2. While M249K showed no association with conventional vascular risk factors, it was consistently associated with a lower risk of myocardial infarction (odds ratio [OR]: 0.66, 95% confidence interval [CI]: 0.54–0.81, p = 6.1 × 10 −5 ) and coronary artery disease (OR: 0.74, 95%CI: 0.63–0.87, p = 2.9 × 10 −4 ) in the UK Biobank and in six replication cohorts. In a phenome-wide association study, there was no evidence of a higher risk of infections among M249K carriers. Conclusions Carriers of an experimentally confirmed damaging CCR2 variant are at a lower lifetime risk of myocardial infarction and coronary artery disease without carrying a higher risk of infections. Our findings provide genetic support for the translational potential of CCR2-targeting as an atheroprotective approach.

Abstract Angina pectoris is associated with adverse cardiovascular events. In this study, a Bi-directional Long Short-Term Memory (Bi-LSTM) prediction model with the Attention layer was established to explore the predictive value of the resting-state RR interval time series on the occurrence of angina pectoris. The data of this cohort study were from the Sleep Heart Health Study database, 2,977 people were included with the follow-up of 15 years. We used the RR interval time series of electrocardiogram signals in the resting state. The outcome variables were any angina events during the follow-up. We randomly divided 2,977 participants into training ( n = 2680) and testing sets ( n = 297) with a partition ratio of 9:1. The prediction model of Bi-LSTM with Attention layer was developed and the predictive performance was assessed. 1,236 had angina pectoris and 1,741 patients did not have angina pectoris during the follow-up period. The predictive performance of the Bi-LSTM model was great with the value of accuracy = 0.913, area under the curve (AUC) = 0.922, precision = 0.913 in the testing set. RR intervals may be the potential predictors of angina events. It is more and more convenient to obtain heart rate with the development of wearable devices; the Bi-LSTM prediction model established in this study is expected to provide support for the intelligent prediction of angina pectoris events.

Integrating multi-omics data may help researchers understand the genetic underpinnings of complex traits and diseases. However, the best ways to integrate multi-omics data and use them to address pressing scientific questions remain a challenge. One important and topical problem is how to assess the aggregate effect of multiple genomic data types (e.g. genotypes and gene expression levels) on a phenotype, particularly while accommodating routine issues, such as having related subjects' data in analyses. In this paper, we extend an existing composite kernel machine regression model to integrate two multi-omics data types, while accommodating for general correlation structures amongst outcomes. Due to the kernel machine regression framework, our methods allow for the integration of high-dimensional omics data with small, nonlinear, and interactive effects, and accommodation of general study designs. Here, we focus on scientific questions that aim to assess the association between a functional grouping (such as a gene or a pathway) and a quantitative trait of interest. We use a kernel machine regression to integrate the two multi-omics data types, as they may relate to the trait, and perform a global test of association. We demonstrate the advantage of this approach over single data type association tests via simulation. Finally, we apply this method to a large, multi-ethnic data set to investigate how predicted gene expression and rare genetic variation may be related to two platelet traits.