GERDH: an interactive multi-omics database for cross-species data mining in horticultural crops.

Horticultural plants contribute immensely to the quality of human's life. The rapid development of omics studies on horticultural plants has resulted in large volumes of valuable growth- and development-related data. Genes that are essential for growth and development are highly conserved in evolution. Cross-species data mining reduces the impact of species heterogeneity and has been extensively used for conserved gene identification. Owing to the lack of a comprehensive database for cross-species data mining using multi-omics data from all horticultural plant species, the current resources in this field are far from satisfactory. Here, we introduce GERDH (https://dphdatabase.com), a database platform for cross-species data mining among horticultural plants, based on 12 961 uniformly processed publicly available omics libraries from more than 150 horticultural plant accessions, including fruits, vegetables and ornamental plants. Important and conserved genes that are essential for a specific biological process can be obtained by cross-species analysis module with interactive web-based data analysis and visualization. Moreover, GERDH is equipped with seven online analysis tools, including gene expression, in-species analysis, epigenetic regulation, gene co-expression, enrichment/pathway and phylogenetic analysis. By interactive cross-species analysis, we identified key genes contributing to postharvest storage. By gene expression analysis, we explored new functions of CmEIN3 in flower development, which was validated by transgenic chrysanthemum analysis. We believe that GERDH will be a useful resource for key gene identification and will allow for omics big data to be more available and accessible to horticultural plant community members.

Integrating plasma proteomes with genome-wide association data for causal protein identification in multiple myeloma.

BACKGROUND: Multiple myeloma (MM) is a severely debilitating and fatal B-cell neoplastic disease. The discovery of disease-associated proteins with causal genetic evidence offers a chance to uncover novel therapeutic targets. METHODS: First, we comprehensively investigated the causal association between 2994 proteins and MM through two-sample mendelian randomization (MR) analysis using summary-level data from public genome-wide association studies of plasma proteome (N = 3301 healthy individuals) and MM (598 cases and 180,756 controls). Sensitivity analyses were performed for these identified causal proteins. Furthermore, we pursued the exploration of enriched biological pathways, prioritized the therapeutic proteins, and evaluated their druggability using the KEGG pathway analysis, MR-Bayesian model averaging analysis, and cross-reference with current databases, respectively. RESULTS: We identified 13 proteins causally associated with MM risk (false discovery rate corrected P < 0.05). Six proteins were positively associated with the risk of MM, including nicotinamide phosphoribosyl transferase (NAMPT; OR [95% CI]: 1.35 [1.18, 1.55]), tyrosine kinase with immunoglobulin-like and EGF-like domains 1 (TIE1; 1.14 [1.06, 1.22]), neutrophil cytosol factor 2 (NCF2; 1.27 [1.12, 1.44]), carbonyl reductase 1, cAMP-specific 3',5'-cyclic phosphodiesterase 4D (PDE4D), platelet-activating factor acetylhydrolase IB subunit beta (PAFAH1B2). Seven proteins were inversely associated with MM, which referred to suppressor of cytokine signaling 3 (SOCS3; 0.90 [0.86, 0.94]), Fc-gamma receptor III-B (FCGR3B; 0.75 [0.65,0.86]), glypican-1 (GPC1; 0.69 [0.58,0.83]), follistatin-related protein 1, protein tyrosine phosphatase non-receptor type 4 (PTPN4), granzyme B, complement C1q subcomponent subunit C (C1QC). Three of the causal proteins, SOCS3, FCGR3B, and NCF2, were enriched in the osteoclast differentiation pathway in KEGG enrichment analyses while GPC1 (marginal inclusion probability (MIP):0.993; model averaged causal effects (MACE): - 0.349), NAMPT (MIP:0.433; MACE: - 0.113), and NCF2 (MIP:0.324; MACE:0.066) ranked among the top three MM-associated proteins according to MR-BMA analyses. Furthermore, therapeutics targeting four proteins are currently under evaluation, five are druggable and four are future breakthrough points. CONCLUSIONS: Our analysis revealed a set of 13 novel proteins, including six risk and seven protective proteins, causally linked to MM risk. The discovery of these MM-associated proteins opens up the possibility for identifying novel therapeutic targets, further advancing the integration of genome and proteome data for drug development.

Global Proteomics for Identifying the Alteration Pathway of Niemann-Pick Disease Type C Using Hepatic Cell Models.

Niemann-Pick disease type C (NPC) is an autosomal recessive disorder with progressive neurodegeneration. Although the causative genes were previously identified, NPC has unclear pathophysiological aspects, and patients with NPC present various symptoms and onset ages. However, various novel biomarkers and metabolic alterations have been investigated; at present, few comprehensive proteomic alterations have been reported in relation to NPC. In this study, we aimed to elucidate proteomic alterations in NPC and perform a global proteomics analysis for NPC model cells. First, we developed two NPC cell models by knocking out NPC1 using CRISPR/Cas9 (KO1 and KO2). Second, we performed a label-free (LF) global proteomics analysis. Using the LF approach, more than 300 proteins, defined as differentially expressed proteins (DEPs), changed in the KO1 and/or KO2 cells, while the two models shared 35 DEPs. As a bioinformatics analysis, the construction of a protein-protein interaction (PPI) network and an enrichment analysis showed that common characteristic pathways such as ferroptosis and mitophagy were identified in the two model cells. There are few reports of the involvement of NPC in ferroptosis, and this study presents ferroptosis as an altered pathway in NPC. On the other hand, many other pathways and DEPs were previously suggested to be associated with NPC, supporting the link between the proteome analyzed here and NPC. Therapeutic research based on these results is expected in the future.

Transcriptomics of receptive endometrium in women with sonographic features of adenomyosis.

BACKGROUND: Women with uterine adenomyosis seeking assisted reproduction have been associated with compromised endometrial receptivity to embryo implantation. To understand the mechanisms involved in this process, we aimed to compare endometrial transcriptome profiles during the window of implantation (WOI) between women with and without adenomyosis. METHODS: We obtained endometrial biopsies LH-timed to the WOI from women with sonographic features of adenomyosis (n=10) and controls (n=10). Isolated RNA samples were subjected to RNA sequencing (RNA-seq) by the Illumina NovaSeq 6000 platform and endometrial receptivity classification with a molecular tool for menstrual cycle phase dating (beREADY®, CCHT). The program language R and Bioconductor packages were applied to analyse RNA-seq data in the setting of the result of accurate endometrial dating. To suggest robust candidate pathways, the identified differentially expressed genes (DEGs) associated with the adenomyosis group in the receptive phase were further integrated with 151, 173 and 42 extracted genes from published studies that were related to endometrial receptivity in healthy uterus, endometriosis and adenomyosis, respectively. Enrichment analyses were performed using Cytoscape ClueGO and CluePedia apps. RESULTS: Out of 20 endometrial samples, 2 were dated to the early receptive phase, 13 to the receptive phase and 5 to the late receptive phase. Comparison of the transcriptomics data from all 20 samples provided 909 DEGs (p<0.05; nonsignificant after adjusted p value) in the adenomyosis group but only 4 enriched pathways (Bonferroni p value < 0.05). The analysis of 13 samples only dated to the receptive phase provided suggestive 382 DEGs (p<0.05; nonsignificant after adjusted p value) in the adenomyosis group, leading to 33 enriched pathways (Bonferroni p value < 0.05). These included pathways were already associated with endometrial biology, such as "Expression of interferon (IFN)-induced genes" and "Response to IFN-alpha". Data integration revealed pathways indicating a unique effect of adenomyosis on endometrial molecular organization (e.g., "Expression of IFN-induced genes") and its interference with endometrial receptivity establishment (e.g., "Extracellular matrix organization" and "Tumour necrosis factor production"). CONCLUSIONS: Accurate endometrial dating and RNA-seq analysis resulted in the identification of altered response to IFN signalling as the most promising candidate of impaired uterine receptivity in adenomyosis.

Microarray-Based Gene Expression Analysis Identifies Potential Diagnostic and Prognostic Biomarkers for Waldenström Macroglobulinemia.

Waldenström macroglobulinemia (WM), also known as lymphoplasmacytic lymphoma, is rare but a clinicopathologically distinct B-cell malignancy. This study assessed differentially expressed genes (DEGs) to identify potential WM biomarkers and uncover the underlying the molecular mechanisms of WM progression using gene expression profiles from the Gene Expression Omnibus database. DEGs were identified using the LIMMA package and their potential functions were then analyzed by using the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses and the protein-protein interaction (PPI) network analysis by using the Search Tool for the Retrieval of Interacting Genes/Proteins database. Data showed that among 1,756 DEGs, 926 were upregulated and 830 were downregulated by comparing WM BM CD19+ with normal PB CD19+ B cell samples, whereas 241 DEGs (95 upregulated and 146 downregulated) were identified by comparing WM BM CD138+ with normal BM CD138+ plasma cell samples. The DEGs were enriched in different GO terms and pathways, including the apoptotic process, cell cycle arrest, immune response, cell adhesion, mitogen-activated protein kinase signaling pathway, toll-like receptor signaling pathway, and the gonadotropin-releasing hormone signaling pathway. Hub nodes in the PPI network included CDK1, JUN, CREBBP, EP300, CAD, CDK2, and MAPK14. Bioinformatics analysis of the GSE9656 dataset identified 7 hub genes that might play an important role in WM development and progression. Some of the candidate genes and pathways may serve as promising therapeutic targets for WM.

Comparative Transcriptome Analysis of Gene Expression and Regulatory Characteristics Associated with Different Vernalization Periods in Brassica rapa.

Brassica rapa is an important Chinese vegetable crop that is beneficial to human health. The primary factor affecting B. rapa yield is low temperature, which promotes bolting and flowering, thereby lowering its commercial value. However, quickened bolting and flowering can be used for rapid breeding. Therefore, studying the underlying molecular mechanism of vernalization in B.rapa is crucial for solving production-related problems. Here, the transcriptome of two B. rapa accessions were comprehensively analyzed during different vernalization periods. During vernalization, a total of 974,584,022 clean reads and 291.28 Gb of clean data were obtained. Compared to the reference genome of B. rapa, 44,799 known genes and 2280 new genes were identified. A self-organizing feature map analysis of 21,035 differentially expressed genes was screened in two B. rapa accessions, 'Jin Wawa' and 'Xiao Baojian'. The analysis indicated that transcripts related to the plant hormone signal transduction, starch and sucrose metabolism, photoperiod and circadian clock, and vernalization pathways changed notably at different vernalization periods. Moreover, different expression patterns of TPS, UGP, CDF, VIN1, and seven hormone pathway genes were observed during vernalization between the two accessions. The transcriptome results of this study provide a new perspective on the changes that occur during B. rapavernalization, as well as serve as an excellent reference for B. rapa breeding.

Genomic analysis of the prognostic value of colony-stimulating factors (CSFs) and colony-stimulating factor receptors (CSFRs) across 24 solid cancer types.

BACKGROUND: The prognostic roles of granulocyte-/granulocyte-macrophage colony-stimulating factor (G-/GM-CSF) and its receptors (CSFRs) from the genomic perspective remain controversial. The aim of our study was to evaluate their prognostic value in multiple cancer types by analyzing omics data. METHODS: The omics data of G-/GM-CSF and receptors were obtained from the cBioportal database. Cutoff values were determined by X-tile. Overall survival (OS) was assessed by Kaplan-Meier curves. Differentially expressed genes (DEGs) and common regulated genes were analyzed using R software and Venny 2.1.0, while enrichment pathway analyses were performed by Metascape. RESULTS: A comprehensive mRNA analysis was performed in 8,565 patients across 24 cancer types. The combination subgroup of CSF2 and its receptors with high expression and favorable prognosis was associated with the activation of immune-related pathways, while the subgroup with unfavorable prognosis was associated with the activation of inflammatory and cellular pathways. As for the combination subgroup of CSF3 and its receptor, the high expression and poor prognosis subgroup was accompanied by the activation of inflammation and signaling transduction pathways. CONCLUSIONS: The prognostic value of CSFs and CSFRs are cancer-type dependent. Therefore, personalized risk stratification based on CSF and CSFR pathway should be considered for cancer patients.

CDH13 and HCRTR2 May Be Associated with Hypersomnia Symptom of Bipolar Depression: A Genome-Wide Functional Enrichment Pathway Analysis.

Although bipolar disorder is highly heritable, the identification of specific genetic variations is limited because of the complex traits underlying the disorder. We performed a genome-wide association study of bipolar disorder using a subphenotype that shows hypersomnia symptom during a major depressive episode. We investigated a total of 2,191 cases, 1,434 controls, and 703,012 single nucleotide polymorphisms (SNPs) in the merged samples obtained from the Translational Genomics Institute and the Genetic Association Information Network. The gene emerging as the most significant by statistical analysis was rs1553441 (odds ratio=0.4093; p=1.20×10(-5); Permuted p=6.0×10(-6)). However, the 5×0(-8) threshold for statistical significance required in a genome-wide association study was not achieved. The functional enrichment pathway analysis showed significant enrichments in the adhesion, development-related, synaptic transmission-related, and cell recognition-related pathways. For further evaluation, each gene of the enriched pathways was reviewed and matched with genes that were suggested to be associated with psychiatric disorders by previous genetic studies. We found that the cadherin 13 and hypocretin (orexin) receptor 2 genes may be involved in the hypersomnia symptom during a major depressive episode of bipolar disorder.