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Whole genome sequence-based association analysis of African American individuals with bipolar disorder and schizophrenia.

In studies of individuals of primarily European genetic ancestry, common and low-frequency variants and rare coding variants have been found to be associated with the risk of bipolar disorder (BD) and schizophrenia (SZ). However, less is known for individuals of other genetic ancestries or the role of rare non-coding variants in BD and SZ risk. We performed whole genome sequencing of African American individuals: 1,598 with BD, 3,295 with SZ, and 2,651 unaffected controls (InPSYght study). We increased power by incorporating 14,812 jointly called psychiatrically unscreened ancestry-matched controls from the Trans-Omics for Precision Medicine (TOPMed) Program for a total of 17,463 controls. To identify variants and sets of variants associated with BD and/or SZ, we performed single-variant tests, gene-based tests for singleton protein truncating variants, and rare and low-frequency variant annotation-based tests with conservation and universal chromatin states and sliding windows. We found suggestive evidence of BD association with single-variants on chromosome 18 and of lower BD risk associated with rare and low-frequency variants on chromosome 11 in a region with multiple BD GWAS loci, using a sliding window approach. We also found that chromatin and conservation state tests can be used to detect differential calling of variants in controls sequenced at different centers and to assess the effectiveness of sequencing metric covariate adjustments. Our findings reinforce the need for continued whole genome sequencing in additional samples of African American individuals and more comprehensive functional annotation of non-coding variants.

Journal Article↗

Rehabilomics Strategies Enabled by Cloud-Based Rehabilitation: Scoping Review.

BACKGROUND: Rehabilomics, or the integration of rehabilitation with genomics, proteomics, metabolomics, and other "-omics" fields, aims to promote personalized approaches to rehabilitation care. Cloud-based rehabilitation offers streamlined patient data management and sharing and could potentially play a significant role in advancing rehabilomics research. This study explored the current status and potential benefits of implementing rehabilomics strategies through cloud-based rehabilitation. OBJECTIVE: This scoping review aimed to investigate the implementation of rehabilomics strategies through cloud-based rehabilitation and summarize the current state of knowledge within the research domain. This analysis aims to understand the impact of cloud platforms on the field of rehabilomics and provide insights into future research directions. METHODS: In this scoping review, we systematically searched major academic databases, including CINAHL, Embase, Google Scholar, PubMed, MEDLINE, ScienceDirect, Scopus, and Web of Science to identify relevant studies and apply predefined inclusion criteria to select appropriate studies. Subsequently, we analyzed 28 selected papers to identify trends and insights regarding cloud-based rehabilitation and rehabilomics within this study's landscape. RESULTS: This study reports the various applications and outcomes of implementing rehabilomics strategies through cloud-based rehabilitation. In particular, a comprehensive analysis was conducted on 28 studies, including 16 (57%) focused on personalized rehabilitation and 12 (43%) on data security and privacy. The distribution of articles among the 28 studies based on specific keywords included 3 (11%) on the cloud, 4 (14%) on platforms, 4 (14%) on hospitals and rehabilitation centers, 5 (18%) on telehealth, 5 (18%) on home and community, and 7 (25%) on disease and disability. Cloud platforms offer new possibilities for data sharing and collaboration in rehabilomics research, underpinning a patient-centered approach and enhancing the development of personalized therapeutic strategies. CONCLUSIONS: This scoping review highlights the potential significance of cloud-based rehabilomics strategies in the field of rehabilitation. The use of cloud platforms is expected to strengthen patient-centered data management and collaboration, contributing to the advancement of innovative strategies and therapeutic developments in rehabilomics.

Cloud Computing↗

Comprehensive Analysis of Clinical and Molecular Features in Cancer Patients Associated With Major Human Oncoviruses.

Viral infections contribute to a higher incidence of cancer than any other individual risk factor. This study aimed to compare the clinical and molecular features of four viral-associated cancers: stomach adenocarcinoma (STAD), head and neck squamous cell carcinoma (HNSC), liver hepatocellular carcinoma (LIHC), and cervical squamous cell carcinoma (CESC). Patients were categorized based on viral infection status, as provided in the clinical data, into virus-associated and non-virus-associated groups, followed by a comprehensive comparison of clinical and molecular features. Our analysis disclosed that viral infections confer unique clinical and molecular signatures to their associated tumors. Specifically, human papillomavirus-associated (HPV+) HNSC and hepatitis B virus-associated (HBV+) LIHC patients were predominantly male, younger, and exhibited better clinical prognoses. Virus-associated tumors displayed enhanced immune microenvironments and high DNA damage response scores, while non-virus-associated tumors were enriched in stromal signatures. HPV+ HNSC and Epstein-Barr virus-associated (EBV+) STAD showed similarities across multi-omics features, including better responses to immunotherapy, lower TP53 mutation rates, tumor mutation burden (TMB), and copy number alteration (CNA). Conversely, HBV+, Hepatitis C virus-associated (HCV+) LIHCs and HPV+ CESC were more genomically unstable due to high TP53 mutation rates, TMB, and CNA. At the protein level, Caspase-7 and Syk were upregulated in HPV+ HNSC and EBV+ STAD, and positively correlated with the enrichment levels of CD8 + T cell, PD-L1, and cytolytic activity. Patient stratification based on infection status has significant clinical implications, particularly for patient prognosis and drug response.

Humans↗

Sec and Tat Mediated Secretion Safeguards Mycobacterium tuberculosis Membrane Homeostasis.

Protein secretion is essential for the growth and virulence of Mycobacterium tuberculosis, yet the organization and function of its secretion pathways remain poorly understood. We reviewed the existing literature, combined it with systematic queries, and finalized annotations based on experimental data and computational predictions to compile a curated list of 92 secretory components and 198 reactions involved in Sec, twin-arginine translocation (Tat), and ESX pathways. Using CRISPRi, targeted depletion of SecA1 or TatAC impaired both in vitro growth and ex vivo survival. Label-free quantitative secretome analysis revealed decreased export of substrates dependent on SecA1 and TatAC, with enrichment of cytosolic proteins in culture filtrates, indicating increased membrane dysbiosis. Membrane proteomics showed elevated levels of proteins engaged in intermediary and lipid metabolism, while proteins associated with the cell wall and cell processes decreased, suggesting weakened membrane integrity. Loss of SecA1 or TatAC increased membrane permeability, with the effect being more pronounced in the case of TatAC, and caused structural abnormalities seen under electron microscopy. Overall, our integrated multi-omics and functional genetics studies demonstrate that the SecA1 and Tat pathways are essential for maintaining membrane homeostasis in Mycobacterium tuberculosis. These results suggest that essential secretory proteins may be promising targets for therapeutic intervention.

Mycobacterium tuberculosis↗

New paradigms in cardiovascular medicine: emerging technologies and practices: perioperative genomics.

Considerable progress has been made in understanding the pathophysiology of perioperative stress responses and their impact on the cardiovascular system; however, researchers are just beginning to unravel genetic and molecular determinants that predispose to increased risk for postoperative cardiovascular adverse events. A new field, coined perioperative genomics, aims to apply functional genomic approaches to uncover the biological reasons why similar patients can have dramatically different clinical outcomes after surgery. For the perioperative physician, such findings may soon translate into prospective risk assessment incorporating genomic profiling of markers important in inflammatory, thrombotic, vascular, and neurologic responses to perioperative stress, with implications ranging from individualized additional pre-operative testing and physiological optimization, to perioperative decision-making, choice of monitoring strategies, and critical care resource utilization. We review current knowledge regarding genomic technologies in perioperative cardiovascular disease characterization and outcome prediction, as well as discuss future trends/challenges for translating integrated "omic" information into daily clinical management of the surgical patient.

Animals↗

H-NOX and NosP Regulate Flagellar Protein and Virulence Factor Production in Vibrio cholerae.

The ability of Vibrio cholerae to transition between motile and sessile forms in the environment and in the host is critical to its survival and virulence. The molecular cues, sensor proteins, and signaling pathways mediating these transitions are highly complex and often overlapping. Nevertheless, a detailed understanding of them is critical for understanding the persistence and pathogenesis of this deadly pathogen. Nitric oxide (NO) functions as an important signaling molecule in many bacteria, affecting biofilm formation, motility, and virulence, often through interaction with heme protein sensors. The genome of V. cholerae encodes two such sensors called H-NOX and NosP. Here we constructed a Δhnox/nosP mutant and employed a multi-omics methodology that combines tandem-mass-tag (TMT)-based quantitative proteomics, phosphoproteomics, and targeted metabolomics to investigate the function of these sensors. A set of 258 proteins was differentially expressed in the mutant that included many proteins involved in flagellar biosynthesis and motility as well as critical virulence factors, iron acquisition systems, and metabolic enzymes. Many of the identified genes are also part of the ferric uptake regulator (Fur) regulon and iron-dependent transcriptional repression of several Fur targets was disrupted. Phosphoproteomics analysis also revealed proteins involved in motility and virulence as differentially phosphorylated in the mutant strain. In most cases, these phosphoproteins have not been previously observed and provide a wealth of new targets for investigating mechanisms of V. cholerae signaling. Taken together, this work illustrates a role for H-NOX and NosP in promoting factors important for infection while suppressing those important for environmental survival, suggesting a function in priming the organism for infection and/or maintaining the infectious phenotype.

Journal Article↗

Lessons from controversy: ovarian cancer screening and serum proteomics.

In 2002 a study reported that a blood test, based on pattern-recognition proteomics mass spectroscopy analysis of serum, was nearly 100% sensitive and specific to detect ovarian cancer. Plans to introduce a commercial screening test by early 2004 were delayed amid concerns about whether the approach was reproducible and reliable. In this issue of JNCI, two commentaries discuss whether the initial results are reproducible and whether bias may account for results. This essay describes how threats to validity from chance and bias may cause erroneous results and inflated expectations in the kind of observational research being conducted in several "-omics" fields to assess molecular markers for diagnosis and prognosis of cancer. To address such threats and to realize the potential of new -omics technology will require application of appropriate rules of evidence in the design, conduct, and interpretation of clinical research about molecular markers.

Biomarkers, Tumor↗

Identification and genetic validation of potential therapeutic targets for pulmonary hypertension through multi-omics causal inference.

Pulmonary hypertension (PH) underscores the urgent need for novel therapeutic targets. This study aimed to employ a proteome-wide Mendelian randomization (MR) approach to systematically identify circulating proteins causally associated with PH, thereby providing genetically validated candidate targets for drug development. We adopted a 2-sample MR design, integrating large-scale plasma proteomic quantitative trait loci (pQTL) data (encompassing 4148 proteins) and summary statistics from a large-scale PH genome-wide association study (2047 cases, 8301 controls). Candidate targets were screened through a multilayered analytical pipeline comprising proteomic MR, transcriptomic MR, and summary-data-based Mendelian randomization. The ultimately identified MR-Identified Causal Candidate Targets (MR-ICTs) underwent rigorous Bayesian colocalization analysis, followed by biological characterization through functional enrichment analysis, single-cell transcriptomics, and phenome-wide association studies. Through robust genetic causal inference, this study provides that circulating proteins such as LYZ, GREM2, NID1, and PF4V1 play causal roles in PH pathogenesis. These findings offer a set of rigorously genetically validated, high-priority therapeutic targets for developing novel PH treatments, specifically addressing key pathological mechanisms such as innate immunity, BMP signaling pathway dysregulation, and platelet activation. Our multi-dimensional analysis ultimately identified 6 MR-ICTs causally associated with PH. Notably, the causal associations for lysozyme C (LYZ), gremlin-2 (GREM2), nidogen-1 (NID1), and platelet factor 4 variant 1 (PF4V1) were stringently validated by Bayesian colocalization analysis (posterior probability for hypothesis 4 [PPH4], indicating a shared causal variant, > 0.99). Functional enrichment analysis revealed significant involvement of these targets in immune response and TGF-β signaling pathways. Single-cell analysis further elucidated their cell-type-specific expression, with LYZ predominantly expressed in monocytes and PF4V1 almost exclusively in platelets.

Hypertension, Pulmonary↗

Multi-omics identification and functional validation of signal regulatory protein gamma as a prognostic biomarker and immune regulator in head and neck squamous cell carcinoma.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) comprises biologically diverse tumors, and durable responses to immune-checkpoint blockade are achieved by only a subset of patients. There remains a need for markers that connect clinical outcome with malignant-cell phenotypes and tissue-level immune organization. METHODS: We integrated The Cancer Genome Atlas HNSCC cohort (TCGA-HNSC), five Gene Expression Omnibus (GEO) validation cohorts, single-cell RNA sequencing, Visium spatial transcriptomics, cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq)-informed protein-potential inference, pharmacogenomic screening, genetic-risk analysis and experimental validation. A reconstructed 296-pipeline survival modelling framework was used to prioritize prognostic hub genes across validation-cohort-specific analyses. RESULTS: SIRPG was repeatedly ranked among the top ten selected genes in all five validation cohorts. At single-cell resolution, SIRPG-high tumor cells showed stronger malignant-cell features, immune-inhibitory and metabolic programs, Scissor-positive risk association, CLCA2/P53-related perturbation signals and inferred SIRPG-CD47/signal regulatory protein (SIRP) communication. Spatial analyses placed this axis within an immune-checkpoint-coupled niche, supported by Maxspin/multiview intercellular spatial modelling (MISTy) spatial coupling, communication analysis by optimal transport (COMMOT)-inferred CD47-SIRPG communication and scProTrans-inferred CD47/SIRPG protein-potential overlap. Functionally, SIRPG knockdown reduced HNSCC cell viability and increased apoptosis, whereas re-expression of short hairpin RNA (shRNA)-resistant SIRPG restored the CLCA2-BAX/BCL2 protein response. CONCLUSION: Together, these findings identify SIRPG as an immune-related prognostic hub and context-dependent tumor-cell regulator associated with apoptosis, immune communication and spatial microenvironmental organization in HNSCC.

Humans↗

scPOEM: robust co-embedding of peaks and genes revealing peak-gene regulation.

MOTIVATION: Identifying regulatory elements in various chromosomal regions that influence gene expression is a fundamental challenge in epigenomics, with profound implications for understanding gene regulation and disease mechanisms. The advent of paired single-cell RNA sequencing and single-cell ATAC sequencing has created unprecedented opportunities to address this challenge by enabling simultaneous profiling of gene expression and chromatin accessibility at single-cell resolution. However, the inherent signals between them are weak due to the highly sparse and noisy nature of data. RESULTS: This article proposes single-cell meta-Path based Omics Embedding (scPOEM), a novel embedding method that jointly projects chromatin accessibility peaks and expressed genes into a shared low-dimensional space. By integrating the relationships among peak-peak, peak-gene, and gene-gene interactions, scPOEM assigns closer representations in the embedding space to related peak-gene pairs. Our experiments demonstrate that scPOEM generates stable representations of peaks and genes, outperforms existing methods in recovering biologically meaningful peak-gene regulatory relationships and enables new insights in subgroup and differential analysis of gene regulation. These results highlight its potential to uncover gene regulatory mechanisms and enhance the understanding of transcriptional regulation at single-cell resolution. AVAILABILITY AND IMPLEMENTATION: The source code of scPOEM is available at https://github.com/Houyt23/scPOEM. The datasets can be obtained from the 10× Genomics (https://www.10xgenomics.com/datasets/pbmc-from-a-healthy-donor-granulocytes-removed-through-cell-sorting-10-k-1-standard-1-0-0) and GEO database under access codes GSE194122 and GSE239916.

Gene Expression Regulation↗

Integrative multi-omics and machine learning identify the SPI1-METTL16-PLIN4 axis as a candidate driver of steatosis in HepG2 cells.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is a prevalent metabolic disorder with limited therapeutic options. This study aimed to identify potential regulators and explore their functional roles in a cellular model of NAFLD. METHODS: WGCNA was performed on the hepatic transcriptomic dataset GSE126848 (31 NAFLD vs. 26 controls), followed by integration with serum proteomic data from 12 NAFLD patients and 12 healthy controls. Hub genes were prioritized using three machine learning algorithms. Functional validation was conducted in a HepG2 cellular steatosis model induced by high fructose (3.2&#x202f;g/L) and oleic acid (400&#x202f;&#x3bc;M) for 48&#x202f;h. Lipid accumulation was assessed by Oil Red O staining and triglyceride/total cholesterol measurement. Inflammation was evaluated by TNF-&#x3b1; and IL-6 secretion (ELISA), and oxidative stress by ROS levels (flow cytometry). The binding interaction between METTL16 and PLIN4 mRNA was validated by RNA immunoprecipitation (RIP)-quantitative PCR. METTL16-mediated m6A modification of PLIN4 was assessed by Methylated RIP (MeRIP)-quantitative PCR. Transcriptional regulation of METTL16 by SPI1 was examined by chromatin immunoprecipitation (ChIP) and dual-luciferase reporter assays. RESULTS: Integrative analysis identified PLIN4 as a core hub gene. PLIN4 was upregulated in the HepG2 steatosis model (P&#x202f;<&#x202f;0.001). PLIN4 knockdown alleviated lipid droplet accumulation (P&#x202f;<&#x202f;0.001), reduced TNF-&#x3b1; and IL-6 secretion (P&#x202f;<&#x202f;0.01), and decreased ROS levels (P&#x202f;<&#x202f;0.001) in fructose/oleic acid-treated HepG2 cells. Mechanistically, METTL16 mediated its m6A modification to enhance PLIN4 mRNA stability. Furthermore, SPI1 was found to transcriptionally activate METTL16 by binding to its promoter (P&#x202f;<&#x202f;0.001). PLIN4 re-expression partially reversed the protective effects of SPI1 knockdown on lipid accumulation (P&#x202f;=&#x202f;0.01), inflammation (P&#x202f;<&#x202f;0.05), and oxidative stress (P&#x202f;<&#x202f;0.001). CONCLUSION: This study identifies the SPI1/METTL16/PLIN4 axis as a potential regulatory mechanism contributing to in vitro steatosis, inflammation, and oxidative stress in steatotic HepG2 cells.

Humans↗

Multi-dimensional profiling of primary metabolites in Heuchera micrantha varieties reveals potential for functional food development.

Heuchera micrantha is a horticultural plant with emerging pharmacological value, yet its primary metabolites remain underexplored. This study comprehensively profiled nutrient metabolites in four H. micrantha varieties using LC-MS/MS. We identified 285 metabolites, with amino acid derivatives being predominant. Multivariate analysis revealed distinct varietal accumulation patterns and 204 differential accumulated metabolites (DAMs). Integrative network pharmacology and molecular docking suggested &#x3b3;-glutamyltyrosine and L-prolyl-L-phenylalanine as potential bioactive dipeptides that may interact with core hubs (MAPK1, EGFR, SRC) involved in cancer and inflammation pathways, though these predictions require experimental validation. Transcriptomics identified 39 differentially expressed genes regulating the biosynthesis of their precursor amino acids. Antioxidant assays showed varietal differences: some excelled in free radical scavenging (DPPH/ABTS) while others demonstrated superior reducing power (FRAP). This multi-omics study suggests that H. micrantha may be a rich source of therapeutically relevant primary metabolites, providing a preliminary scientific basis for its development as a functional food or nutraceutical pending further validation.

Functional Food↗

Clustering individuals using INMTD: a novel versatile multi-view embedding framework integrating omics and imaging data.

MOTIVATION: Combining omics and images can lead to a more comprehensive clustering of individuals than classic single-view approaches. Among the various approaches for multi-view clustering, nonnegative matrix tri-factorization (NMTF) and nonnegative Tucker decomposition (NTD) are advantageous in learning low-rank embeddings with promising interpretability. Besides, there is a need to handle unwanted drivers of clusterings (i.e. confounders). RESULTS: In this work, we introduce a novel multi-view clustering method based on NMTF and NTD, named INMTD, which integrates omics and 3D imaging data to derive unconfounded subgroups of individuals. According to the adjusted Rand index, INMTD outperformed other clustering methods on a synthetic dataset with known clusters. In the application to real-life facial-genomic data, INMTD generated biologically relevant embeddings for individuals, genetics, and facial morphology. By removing confounded embedding vectors, we derived an unconfounded clustering with better internal and external quality; the genetic and facial annotations of each derived subgroup highlighted distinctive characteristics. In conclusion, INMTD can effectively integrate omics data and 3D images for unconfounded clustering with biologically meaningful interpretation. AVAILABILITY AND IMPLEMENTATION: INMTD is freely available at https://github.com/ZuqiLi/INMTD.

Cluster Analysis↗

Soluble Immune Checkpoint Protein and Lipid Network Associations with All-Cause Mortality Risk: Trans-Omics for Precision Medicine (TOPMed) Program.

Adverse cardiovascular events are emerging with the use of immune checkpoint therapies in oncology. Using datasets in the Trans-Omics for Precision Medicine program (Multi-Ethnic Study of Atherosclerosis, Jackson Heart Study [JHS], and Framingham Heart Study), we examined the association of immune checkpoint plasma proteins with each other, their associated protein network with high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C), and the association of HDL-C- and LDL-C-associated protein networks with all-cause mortality risk. Plasma levels of LAG3 and HAVCR2 showed statistically significant associations with mortality risk. Colocalization analysis using genome wide-association studies of HDL-C or LDL-C and protein quantitative trait loci from JHS and the Atherosclerosis Risk in Communities identified TFF3 rs60467699 and CD36 rs3211938 variants as significantly colocalized with HDL-C; in contrast, none colocalized with LDL-C. The measurement of plasma LAG3, HAVCR2, and associated proteins plus targeted genotyping may identify patients at increased mortality risk.

Journal Article↗

Impact of microarray technology in nutrition and food research.

Microarrays have become standard tools for gene expression profiling as the mRNA levels of a large number of genes can be measured in a single assay. Many technical aspects concerning microarray production and laboratory usage have been addressed in great detail, but it remains still crucial to establish this technology in new research fields such as human nutrition and food-related areas. The correlation between diet and inter-individual variation in gene expression is an important and relatively unexplored issue in human nutrition. Therefore, nutritionists changed their research field dramatically from epidemiology and physiology towards the "omics" sciences. Nutrigenomics as a field of research is based on the complete knowledge of the human genome and refers to the entire spectrum of human genes that determine the interactions of nutrition with the organism. Nutrigenetics is based on the inter-individual, genetically determined differences in metabolism. Nutrigenomics and nutrigenetics carry the hope that individualized diet can improve human health and prevent nutrition-related diseases. In this article we give an overview of current DNA and protein microarray techniques (including fabrication, experimental procedure and data analysis), we describe their applications to nutrition and food research and point out the limitations, problems and pitfalls of microarray experiments.

Confidentiality↗

Multi-Omics Genome-Wide to Explore the Formation and Development Targets for Intracranial Aneurysms.

Intracranial aneurysms (IAs) represent a significant and potentially life-threatening category of disease, and there is currently a lack of effective treatment options aimed at preventing the progression of the disease. Accordingly, this study is dedicated to exploring and identifying effective drug targets that can help in the prevention of both the formation and rupture of IAs, along with a detailed examination of the underlying potential mechanisms involved in these processes. The data related to IAs for this research was obtained from the ISGC Biobank and UK Biobank. Then, we investigated the possible biological functions and unintended consequences of targeting the specific genes that were highlighted in IAs by using mediation analysis, virtual knockout experiments, and PW-MR studies. A total of 5 unique potential drug targets for IAs (FKTN, MAP3K1, PSMA4, SLC22A4, ADAM17), 4 unique potential drug targets for SAH (PSMA4, ADAM17, GPR160, SLC22A4), and 2 unique potential drug targets for UIA (SLC22A4, PRCP) were identified across brain or blood samples. Among the various candidates identified, SLC22A4 has emerged as a promising potential drug target, showing significant expression levels in both blood and brain tissues. Additionally, phenome-wide MR of SLC22A4 across 32 selected phenotypes did not identify statistically significant adverse associations after FDR correction. Virtual knockout (KO) experiments on SLC22A4 revealed that SLC22A4 KO disrupted 81 genes, all of which are involved in IAs-related pathways. Besides, we recognized BRD-K85337334 as potential candidates for targeting SLC22A4. This research indicates that an increase in SLC22A4 gene expression within the blood or brain is directly linked to a heightened risk of IAs rupture, which will aid in prioritizing the development of drugs for IAs.

Humans↗

Multi-omics analyses provide insights into the molecular basis for salt tolerance of Phyla nodiflora.

The perennial herbaceous plant, Phyla nodiflora (Verbenaceae), which possesses natural resistance to multiple abiotic stresses, is widely used as a pioneer species in island ecological restoration. Due to the lack of information about its genome, the mechanism underlying its tolerance to environmental stresses, such as salinity, is almost entirely unknown. Here, we report on the high-quality genome of P. nodiflora that is 403.07&#x2009;Mb in size, and which was assembled and anchored onto 18 pseudo-chromosomes. Genomic synteny revealed that P. nodiflora underwent two whole genome duplication events, which promoted the expansion of genes related to environmental adaptation and the biosynthesis of secondary metabolites. An integrated genomic and transcriptomic analysis suggested that salt stress tolerance in P. nodiflora is associated with the expansion and activated expression of genes related to abscisic acid (ABA) homeostasis and signaling. The expansion of ZEP family genes may contribute to the consistent increase in ABA levels under salt stress. Lysine acetylomic analysis revealed that exposure to salt led to widespread protein deacetylation, with these proteins primarily involved in signal transduction, carbohydrate transport and metabolism, and transcription regulation. Deacetylation of glutathione S-transferase increased enzymatic activities in response to salt-induced oxidative stress. Collectively, the genomic, transcriptomic, and lysine acetylomic analyses provide profound insight into the molecular basis of the adaptation of P. nodiflora to salt stress, and will be helpful to engineer salt-tolerant plants for ecological restoration.

Salt Tolerance↗

Are histochemistry and cytochemistry 'Omics'?

A plethora of new 'omics such as transcriptomics, proteomics, metabolomics (or metabonomics), pharmacogenomics, physiomics and cytomics are upon us, but can histochemistry be an 'omic? To be an 'omic a technique must take a 'global' and 'holistic' view of biology that addresses biological complexity head-on by synthesising multiparameter data into predictive models. Thus to be an 'omic, a histochemical technique should be as inclusive as possible in identifying as many targets as possible with equal likelihood and sensitivity of detection. Any technique capable of detecting only one or two targets is not within the spirit of an 'omic, ruling out it seems most of histochemistry. Nevertheless, new developments in high-throughput histochemistry and cytochemistry are making powerful claims to the title 'Histocytomics'. Histocytomics and all the other 'omics are components of the only real 'omic 'Biomics', that is, the integrated application of science into a coherent strategy for understanding biological complexity. In this paper, this strategy is presented for the investigation of the regulation of phenotypic change in skeletal and cardiac muscle in health and disease.

Computational Biology↗