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Abstract Background Phloem protein 2 (PP2) proteins play a vital role in the Phloem-based defense (PBD) and participate in many abiotic and biotic stress. However, research on PP2 proteins in cotton is still lacking. Results A total of 25, 23, 43, and 47 PP2 genes were comprehensively identified and characterized in G.arboretum, G.raimondii, G.barbadense, and G.hirsutum. The whole genome duplication (WGD) and allopolyploidization events play essential roles in the expansion of PP2 genes. The promoter regions of GhPP2 genes contain many cis-acting elements related to abiotic stress and the weighted gene co-expression network analysis (WGCNA) analysis displayed that GhPP2s could be related to salt stress. The qRT-PCR assays further confirmed that GhPP2-33 could be dramatically upregulated during the salt treatment. And the virus-induced gene silencing (VIGS) experiment proved that the silencing of GhPP2-33 could decrease salt tolerance. Conclusions The results in this study not only offer new perspectives for understanding the evolution of PP2 genes in cotton but also further explore their function under salt stress.

The caleosin (CLO) protein family displays calcium-binding properties and plays an important role in the abiotic stress response. Here, a total of 107 CLO genes were identified in 15 plant species, while no CLO genes were detected in two green algal species. Evolutionary analysis revealed that the CLO gene family may have evolved mainly in terrestrial plants and that biological functional differentiation between species and functional expansion within species have occurred. Of these, 56 CLO genes were identified in four cotton species. Collinearity analysis showed that CLO gene family expansion mainly occurred through segmental duplication and whole-genome duplication in cotton. Sequence alignment and phylogenetic analysis showed that the CLO proteins of the four cotton species were mainly divided into two types: H-caleosins (class I) and L-caleosins (class II). Cis-acting element analysis and quantitative RT–PCR (qRT–PCR) suggested that GhCLOs might be regulated by abscisic acid (ABA) and methyl jasmonate (MeJA). Moreover, transcriptome data and qRT–PCR results revealed that GhCLO genes responded to salt and drought stresses. Under salt stress, gene-silenced plants (TRV: GhCLO06) showed obvious yellowing and wilting, higher malondialdehyde (MDA) content accumulation, and significantly lower activities of superoxide dismutase (SOD) and peroxidase (POD), indicating that GhCLO06 plays a positive regulatory role in cotton salt tolerance. In gene-silenced plants (TRV: GhCLO06), ABA-related genes (GhABF2, GhABI5, and GhNAC4) were significantly upregulated after salt stress, suggesting that the regulation of salt tolerance may be related to the ABA signaling pathway. This research provides an important reference for further understanding and analyzing the molecular regulatory mechanism of CLOs for salt tolerance.

Soil salinization conditions seriously restrict cotton yield and quality. Related studies have shown that the DUF4228 proteins are pivotal in plant resistance to abiotic stress. However, there has been no systematic identification and analysis of the DUF4228 gene family in cotton and their role in abiotic stress. In this study, a total of 308 DUF4228 genes were identified in four Gossypium species, which were divided into five subfamilies. Gene structure and protein motifs analysis showed that the GhDUF4228 proteins were conserved in each subfamily. In addition, whole genome duplication (WGD) events and allopolyploidization might play an essential role in the expansion of the DUF4228 genes. Besides, many stress-responsive (MYB, MYC) and hormone-responsive (ABA, MeJA) related cis-elements were detected in the promoters of the DUF4228 genes. The qRT-PCR results showed that GhDUF4228 genes might be involved in the response to abiotic stress. VIGS assays and the measurement of relative water content (RWC), Proline content, POD activity, and malondialdehyde (MDA) content indicated that GhDUF4228-67 might be a positive regulator of cotton response to salt stress. The results in this study systematically characterized the DUF4228s in Gossypium species and will provide helpful information to further research the role of DUF4228s in salt tolerance.

Climate change severely affects crop production. Cotton is one of the primary fiber crops in the world and its production is susceptible to various environmental stresses, especially drought and salinity. Development of stress tolerant genotypes is the only way to escape from these environmental constraints. We identified sixteen homologs of the Arabidopsis JUB1 gene in cotton. Expression of GhJUB1_3‐At was significantly induced in the temporal expression analysis of GhJUB1 genes in the roots of drought tolerant (H177) and susceptible (S9612) cotton genotypes under drought. The silencing of the GhJUB1_3‐At gene alone and together with its paralogue GhJUB1_3‐Dt reduced the drought tolerance in cotton plants. The transgenic lines exhibited tolerance to the drought and salt stress as compared to the wildtype (WT). The chlorophyll and relative water contents of wildtype decreased under drought as compared to the transgenic lines. The transgenic lines showed decreased H2O2 and increased proline levels under drought and salt stress, as compared to the WT, indicating that the transgenic lines have drought and salt stress tolerance. The expression analysis of the transgenic lines and WT revealed that GAI was upregulated in the transgenic lines in normal conditions as compared to the WT. Under drought and salt treatment, RAB18 and RD29A were strongly upregulated in the transgenic lines as compared to the WT. Conclusively, GhJUB1_3‐At is not an auto activator and it is regulated by the crosstalk of GhHB7, GhRAP2‐3 and GhRAV1. GhRAV1, a negative regulator of abiotic stress tolerance and positive regulator of leaf senescence, suppresses the expression of GhJUB1_3‐At under severe circumstances leading to plant death. [ABSTRACT FROM AUTHOR]

Abstract Background Human cytomegalovirus (HCMV) is a herpesvirus that can infect various cell types and modulate host gene expression and immune response. It has been associated with the pathogenesis of various cancers, but its molecular mechanisms remain elusive. Methods We comprehensively analyzed the expression of HCMV pathway genes across 26 cancer types using the Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression (GTEx) databases. We also used bioinformatics tools to study immune invasion and tumor microenvironment in pan-cancer. Cox regression and machine learning were used to analyze prognostic genes and their relationship with drug sensitivity. Results We found that HCMV pathway genes are widely expressed in various cancers. Immune infiltration and the tumor microenvironment revealed that HCMV is involved in complex immune processes. We obtained prognostic genes for 25 cancers and significantly found 23 key genes in the HCMV pathway, which are significantly enriched in cellular chemotaxis and synaptic function and may be involved in disease progression. Notably, CaM family genes were up-regulated and AC family genes were down-regulated in most tumors. These hub genes correlate with sensitivity or resistance to various drugs, suggesting their potential as therapeutic targets. Conclusions Our study has revealed the role of the HCMV pathway in various cancers and provided insights into its molecular mechanism and therapeutic significance. It is worth noting that the key genes of the HCMV pathway may open up new doors for cancer prevention and treatment.

Abstract Objective This study aimed to construct a coronary heart disease (CHD) risk-prediction model in people living with human immunodeficiency virus (PLHIV) with the help of machine learning (ML) per electronic medical records (EMRs). Methods Sixty-one medical characteristics (including demography information, laboratory measurements, and complicating disease) readily available from EMRs were retained for clinical analysis. These characteristics further aided the development of prediction models by using seven ML algorithms [light gradient-boosting machine (LightGBM), support vector machine (SVM), eXtreme gradient boosting (XGBoost), adaptive boosting (AdaBoost), decision tree, multilayer perceptron (MLP), and logistic regression]. The performance of this model was assessed using the area under the receiver operating characteristic curve (AUC). Shapley additive explanation (SHAP) was further applied to interpret the findings of the best-performing model. Results The LightGBM model exhibited the highest AUC (0.849; 95% CI, 0.814–0.883). Additionally, the SHAP plot per the LightGBM depicted that age, heart failure, hypertension, glucose, serum creatinine, indirect bilirubin, serum uric acid, and amylase can help identify PLHIV who were at a high or low risk of developing CHD. Conclusion This study developed a CHD risk prediction model for PLHIV utilizing ML techniques and EMR data. The LightGBM model exhibited improved comprehensive performance and thus had higher reliability in assessing the risk predictors of CHD. Hence, it can potentially facilitate the development of clinical management techniques for PLHIV care in the era of EMRs.

Abstract Background Few studies are focusing on the mechanism of erastin acts on prostate cancer (PCa) cells, and essential ferroptosis-related genes (FRGs) that can be PCa therapeutic targets are rarely known. Methods In this study, in vitro assays were performed and RNA-sequencing was used to measure the expression of differentially expressed genes (DEGs) in erastin-induced PCa cells. A series of bioinformatic analyses were applied to analyze the pathways and DEGs. Results Erastin inhibited the expression of SLC7A11 and cell survivability in LNCaP and PC3 cells. After treatment with erastin, the concentrations of malondialdehyde (MDA) and Fe2+ significantly increased, whereas the glutathione (GSH) and the oxidized glutathione (GSSG) significantly decreased in both cells. A total of 295 overlapping DEGs were identified under erastin exposure and significantly enriched in several pathways, including DNA replication and cell cycle. The percentage of LNCaP and PC3 cells in G1 phase was markedly increased in response to erastin treatment. For four hub FRGs, TMEFF2 was higher in PCa tissue and the expression levels of NRXN3, CLU, and UNC5B were lower in PCa tissue. The expression levels of SLC7A11 and cell survivability were inhibited after the knockdown of TMEFF2 in androgen-dependent cell lines (LNCaP and VCaP) but not in androgen-independent cell lines (PC3 and C4-2). The concentration of Fe2+ only significantly increased in TMEFF2 downregulated LNCaP and VCaP cells. Conclusion TMEFF2 might be likely to develop into a potential ferroptosis target in PCa and this study extends our understanding of the molecular mechanism involved in erastin-affected PCa cells.

Abstract Human endogenous retroviruses (HERVs) are the remnants of ancient retroviral infections integrated into the human genome. Although most HERVs are silenced or rendered inactive by various regulatory mechanisms, they retain the potential to influence the nearby genes. We analyzed the regulatory map of 91 HERV-Ks on neighboring genes in human breast cancer and investigated the impact of HERV-Ks on the tumor microenvironment (TME) and prognosis of breast cancer. Nine RNA-seq datasets were obtained from GEO and NCBI SRA. Differentially expressed genes and HERV-Ks were analyzed using DESeq2. Validation of high-risk prognostic candidate genes using TCGA data. These included Overall survival (multivariate Cox regression model), immune infiltration analysis (TIMER), tumor mutation burden (maftools), and drug sensitivity analysis (GSCA). A total of 88 candidate genes related to breast cancer prognosis were screened, of which CD48, SLAMF7, SLAMF1, IGLL1, IGHA1, and LRRC8A were key genes. Functionally, these six key genes were significantly enriched in some immune function-related pathways, which may be associated with poor prognosis for breast cancer (p = 0.00016), and the expression levels of these genes were significantly correlated with the sensitivity of breast cancer treatment-related drugs. Mechanistically, they may influence breast cancer development by modulating the infiltration of various immune cells into the TME. We further experimentally validated these genes to confirm the results obtained from bioinformatics analysis. This study represents the first report on the regulatory potential of HERV-K in the neighboring breast cancer genome. We identified three key HERV-Ks and five neighboring genes that hold promise as novel targets for future interventions and treatments for breast cancer.