Transcriptional profile and immune infiltration in colorectal cancer reveal the significance of inducible T-cell costimulator as a crucial immune checkpoint molecule

BACKGROUND

Emergence of novel immuno-therapeutics has shown promising improvement in the clinical outcome of colorectal cancer (CRC).

OBJECTIVE

To identify robust immune checkpoints based on expression and immune infiltration profiles of clinical CRC samples.

METHODS

One dataset from The Cancer Genome Atlas database and two from Gene Expression Omnibus were independently employed for the analysis. Genes associated with overall survival were identified, and distribution of each immune checkpoint with respect to different clinical features was determined to explore key immune checkpoints. Multiple staining methods were used to verify the correlation between key immune checkpoint ICOS and clinical pathological features. Differentially expressed mRNA and long non-coding RNA (lncRNA) were then detected for gene set enrichment analysis and gene set variation analysis to investigate the differentially enriched biological processes between low- and high-expression groups. Significant immune-related mRNAs and lncRNA were subjected to competing endogenous RNA (ceRNA) network analysis. Correlation of inducible T-cell costimulator (ICOS) and top 10 genes in ceRNA network were further considered for validation.

RESULTS

ICOS was identified from 14 immune checkpoints as the most highly correlated gene with survival and clinical features in CRC. The expression of ICOS protein in the poorly differentiated group was lower than that in the moderately differentiated group, and the expression in different pathological stages was significant. In addition, the expressions of ICOS were negatively correlated with Ki67. A conspicuous number of immune-related pathways were enriched in differentially expressed genes in the ICOS high- and low-expression groups. Integration with immune infiltration data revealed a multitude of differentially expressed immune-related genes enriched for ceRNA network. Furthermore, expression of top 10 genes investigated from ceRNA network showed high correlation with ICOS.

CONCLUSION

ICOS might serve as a robust immune checkpoint for prognosis with several genes being potential targets of ICOS-directed immunotherapy in CRC.

Transcriptomic Integration Analyses Uncover Common Bisphenol A Effects Across Species and Tissues Primarily Mediated by Disruption of JUN/FOS, EGFR, ER, PPARG, and P53 Pathways

Bisphenol A (BPA) is a common endocrine disruptor widely used in the production of electronic, sports, and medical equipment, as well as consumer products like milk bottles, dental sealants, and thermal paper. Despite its widespread use, current assessments of BPA exposure risks remain limited due to the lack of comprehensive cross-species comparative analyses. To address this gap, we conducted a study aimed at identifying genes and fundamental molecular processes consistently affected by BPA in various species and tissues, employing an effective data integration method and bioinformatic analyses. Our findings revealed that exposure to BPA led to significant changes in processes like lipid metabolism, proliferation, and apoptosis in the tissues/cells of mammals, fish, and nematodes. These processes were found to be commonly affected in adipose, liver, mammary, uterus, testes, and ovary tissues. Additionally, through an in-depth analysis of signaling pathways influenced by BPA in different species and tissues, we observed that the JUN/FOS, EGFR, ER, PPARG, and P53 pathways, along with their downstream key transcription factors and kinases, were all impacted by BPA. Our study provides compelling evidence that BPA indeed induces similar toxic effects across different species and tissues. Furthermore, our investigation sheds light on the underlying molecular mechanisms responsible for these toxic effects. By uncovering these mechanisms, we gain valuable insights into the potential health implications associated with BPA exposure, highlighting the importance of comprehensive assessments and awareness of this widespread endocrine disruptor.

Proteomic and metabolomic characterizations of moyamoya disease patient sera

BACKGROUND

The pathogenesis of moyamoya disease (MMD) is unclear. Inflammation and immune imbalance have been identified as potential factors contributing to the occurrence and progression of MMD. However, the specific proteins and metabolites responsible for triggering this process are yet to be established. The purpose of this study is to identify differentially expressed proteins and metabolites in patients with MMD and perform Kyoto Encyclopedia of Genes and Genomes pathway integration analysis to pinpoint crucial proteins and metabolites involved in the disease.

METHODS

We performed untargeted metabolomic and data-independent acquisition proteomic analyses on the serum samples of individuals with MMD and healthy controls (HC).

RESULTS

In patients with MMD versus HC, 24 proteins and 60 metabolites, including 21 anionic metabolites and 39 cationic metabolites, which were significantly different, were identified. In patients with MMD, several proteins involved in inflammation and immune metabolism, such as tubulin beta-6 and complement C4, were found to have significantly altered levels. Similarly, many metabolites involved in inflammation and immune metabolisms, such as dimethyl 4-hydroxyisophthalate, beta-nicotinamide mononucleotide, 2-(3-(4-pyridyl)-1H-1,2,4-triazol-5-yl)pyridine, and PC (17:1/18:2), were significantly altered. Intriguingly, these proteins and metabolites are involved in the progression of atherosclerosis through immune and inflammatory pathways, although some have never been reported in MMD. Moreover, integrated proteomics and metabolomics studies were conducted to determine shared pathways involving cholesterol metabolism, vitamin digestion, fat digestion, and absorption pathways of proteins and metabolites, which warrant further investigation.

CONCLUSIONS

Significant increases in pro-inflammatory and immunosuppressive abilities have been observed in patients with MMD, accompanied by significant reductions in anti-inflammatory and immune regulation. Various metabolites and proteins implicated in these processes have been identified for the first time. These findings hold immense significance for comprehending the pathogenesis of MMD and for the development of future drug therapies.

Study protocol: Identification and validation of integrative biomarkers of physical activity level and health in children and adolescents (INTEGRActiv)

Background

Physical activity (PA) provides health benefits across the lifespan and improves many established cardiovascular risk factors that have a significant impact on overall mortality. However, discrepancies between self-reported and device-based measures of PA make it difficult to obtain consistent results regarding PA and its health effects. Moreover, PA may produce different health effects depending on the type, intensity, duration, and frequency of activities and individual factors such as age, sex, body weight, early life conditions/exposures, etc. Appropriate biomarkers relating the degree of PA level with its effects on health, especially in children and adolescents, are required and missing. The main objective of the INTEGRActiv study is to identify novel useful integrative biomarkers of PA and its effects on the body health in children and adolescents, who represent an important target population to address personalized interventions to improve future metabolic health.

Methods/design

The study is structured in two phases. First, biomarkers of PA and health will be identified at baseline in a core cohort of 180 volunteers, distributed into two age groups: prepubertal (n = 90), and postpubertal adolescents (n = 90). Each group will include three subgroups (n = 30) with subjects of normal weight, overweight, and obesity, respectively. Identification of new biomarkers will be achieved by combining physical measures (PA and cardiorespiratory and muscular fitness, anthropometry) and molecular measures (cardiovascular risk factors, endocrine markers, cytokines and circulating miRNA in plasma, gene expression profile in blood cells, and metabolomics profiling in plasma). In the second phase, an educational intervention and its follow-up will be carried out in a subgroup of these subjects (60 volunteers), as a first validation step of the identified biomarkers.

Discussion

The INTEGRActiv study is expected to provide the definition of PA and health-related biomarkers (PA-health biomarkers) in childhood and adolescence. It will allow us to relate biomarkers to factors such as age, sex, body weight, sleep behavior, dietary factors, and pubertal status and to identify how these factors quantitatively affect the biomarkers' responses. Taken together, the INTEGRActiv study approach is expected to help monitor the efficacy of interventions aimed to improve the quality of life of children/adolescents through physical activity.

Clinical Trial Registration

ClinicalTrials.gov, Identifier NCT05907785.

Molecular Regulation of Differential Lipid Molecule Accumulation in the Intramuscular Fat and Abdominal Fat of Chickens

Reducing abdominal fat (AF) accumulation and increasing the level of intramuscular fat (IMF) simultaneously is a major breeding goal in the poultry industry. To explore the different molecular mechanisms underlying AF and IMF, gene expression profiles in the breast muscle (BM) and AF from three chicken breeds were analyzed. A total of 4737 shared DEGs were identified between BM and AF, of which 2602 DEGs were upregulated and 2135 DEGs were downregulated in the BM groups compared with the AF groups. DEGs involved in glycerophospholipid metabolism and glycerolipid metabolism were potential regulators, resulting in the difference in lipid metabolite accumulation between IMF and AF. The PPAR signaling pathway was the most important pathway involved in tissue-specific lipid deposition. Correlation analysis showed that most representative DEGs enriched in the PPAR signaling pathway, such as FABP5, PPARG, ACOX1, and GK2, were negatively correlated with PUFA-enriched glycerophospholipid molecules. Most DEGs related to glycerophospholipid metabolism, such as GPD2, GPD1, PEMT, CRLS1, and GBGT1, were positively correlated with glycerophospholipid molecules, especially DHA- and arachidonic acid (ARA)-containing glycerophospholipid molecules. This study elucidated the molecular mechanism underlying tissue-specific lipid deposition and poultry meat quality.

Proteome and genome integration analysis of obesity

ABSTRACT

The prevalence of obesity has increased worldwide in recent decades. Genetic factors are now known to play a substantial role in the predisposition to obesity and may contribute up to 70% of the risk for obesity. Technological advancements during the last decades have allowed the identification of many hundreds of genetic markers associated with obesity. However, the transformation of current genetic variant-obesity associations into biological knowledge has been proven challenging. Genomics and proteomics are complementary fields, as proteomics extends functional analyses. Integrating genomic and proteomic data can help to bridge a gap in knowledge regarding genetic variant-obesity associations and to identify new drug targets for the treatment of obesity. We provide an overview of the published papers on the integrated analysis of proteomic and genomic data in obesity and summarize four mainstream strategies: overlap, colocalization, Mendelian randomization, and proteome-wide association studies. The integrated analyses identified many obesity-associated proteins, such as leptin, follistatin, and adenylate cyclase 3. Despite great progress, integrative studies focusing on obesity are still limited. There is an increased demand for large prospective cohort studies to identify and validate findings, and further apply these findings to the prevention, intervention, and treatment of obesity. In addition, we also discuss several other potential integration methods.

Corrigendum: Integrated analysis of small RNAs, transcriptome and degradome sequencing reveal the drought stress network in Agropyron mongolicum Keng

[This corrects the article DOI: 10.3389/fpls.2022.976684.].

Integrative Analysis Reveals the Expression Pattern of SOX9 in Satellite Glial Cells after Sciatic Nerve Injury

BACKGROUND

Several complex cellular and gene regulatory processes are involved in peripheral nerve repair. This study uses bioinformatics to analyze the differentially expressed genes (DEGs) in the satellite glial cells of mice following sciatic nerve injury.

METHODS

R software screens differentially expressed genes, and the WebGestalt functional enrichment analysis tool conducts Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomics (KEGG) pathway analysis. The Search Tool for the Retrieval of Interacting Genes/Proteins constructs protein interaction networks, and the cytoHubba plug-in in the Cytoscape software predicts core genes. Subsequently, the sciatic nerve injury model of mice was established and the dorsal root ganglion satellite glial cells were isolated and cultured. Satellite glial cells-related markers were verified by immunofluorescence staining. Real-time polymerase chain reaction assay and Western blotting assay were used to detect the mRNA and protein expression of Sox9 in satellite glial cells.

RESULTS

A total of 991 DEGs were screened, of which 383 were upregulated, and 508 were downregulated. The GO analysis revealed the processes of biosynthesis, negative regulation of cell development, PDZ domain binding, and other biological processes were enriched in DEGs. According to the KEGG pathway analysis, DEGs are primarily involved in steroid biosynthesis, hedgehog signaling pathway, terpenoid backbone biosynthesis, American lateral skeleton, and melanoma pathways. According to various cytoHubba algorithms, the common core genes in the protein-protein interaction network are Atf3, Mmp2, and Sox9. Among these, Sox9 was reported to be involved in the central nervous system and the generation and development of astrocytes and could mediate the transformation between neurogenic and glial cells. The experimental results showed that satellite glial cell marker GS were co-labeled with Sox9; stem cell characteristic markers Nestin and p75NTR were labeled satellite glial cells. The mRNA and protein expression of Sox9 in satellite glial cells were increased after sciatic nerve injury.

CONCLUSIONS

In this study, bioinformatics was used to analyze the DEGs of satellite glial cells after sciatic nerve injury, and transcription factors related to satellite glial cells were screened, among which Sox9 may be associated with the fate of satellite glial cells.

Integrated Proteotranscriptomics of the Hypothalamus Reveals Altered Regulation Associated with the FecB Mutation in the BMPR1B Gene That Affects Prolificacy in Small Tail Han Sheep

The litter size and ovulation rate are different among ewes of different FecB genotypes in Small Tail Han sheep. These variants in reproductive phenotypes may be regulated by hormones released by the hypothalamic-pituitary-ovarian axis. However, there have been few reports on the hypothalamus regarding regulating an increase in ovulation in sheep with FecB mutation at different estrous stages. Thus, we examined the abundance of hypothalamus tissue protein profiles of six FecB mutant homozygous (BB) and six wild-type (WW) ewes at the luteal and follicular phases. We determined this abundance by tandem mass tag-based quantitative analysis and parallel reaction monitoring methods. Furthermore, an integrated proteotranscriptomic analysis was performed by the Data Integration Analysis for Biomarker discovery using the latent variable approaches for Omics studies (DIABLO) framework to examine biological processes and pathway alterations by the FecB mutant. The abundance of 154 proteins was different between the two estrous stages. Growth hormone and prolactin were particularly enriched in the neuroactive ligand-receptor interactions, the prolactin signaling pathway, and the PI3K-Akt signaling pathway which are related to hypothalamic function and reproduction. We combined proteome and transcriptome data from different estrous stages and genotypes. There is a high correlation (Pearson correlation coefficient = 0.99) between the two datasets in the first two components. We applied the traditional single-omic multivariate approach to obtain differentially abundant proteins and differentially expressed genes. The major fertility related biomarkers were selected using the two approaches mentioned above. Several key pathways (GABAergic synapse, neuroactive ligand-receptor interaction, estrogen and MAPK signaling pathways) were enriched, which are central to gonadotrophin-releasing hormone (GnRH) secretion and reproduction. A higher level of gamma-aminobutyric acid type A receptor subunit alpha1 (GABRA1) and gamma-aminobutyric acid type A receptor subunit beta2 (GABRB2) expression was observed in BB ewes as compared to WW ewes. This finding suggested that a greater production of GnRH during follicular development in BB ewes may explain the higher mature follicle number in mutant ewes. FKBP prolyl isomerase 1A (FKBP1A), which was a major feature factor in the proteome selected by DIABLO, was an important switch for activating the transforming growth factor beta (TGFβ) pathway, and its expression was higher in the WW ewes than in the BB ewes. We suggest that BB sheep maintain TGFβ pathway activity by reducing FKBP1A protein abundance. This innovative data integration in the hypothalamus may provide fresh insight into the mechanisms by which the FecB mutation affects sheep fertility, while providing novel biomarkers related to reproductive endocrinology in sheep breeding.

Identification of immune cell function in breast cancer by integrating multiple single-cell data

Breast cancer has now become the most commonly diagnosed cancer worldwide. It is a highly complex and heterogeneous disease that comprises distinct histological features and treatment response. With the development of molecular biology and immunology, immunotherapy has become a new field of breast cancer treatment. Identifying cell-type-specific genes critical to the immune microenvironment contributes to breast cancer treatment. Single-cell RNA sequencing (scRNA-seq) technology could serve as a powerful tool to analyze cellular genetic information at single-cell resolution and to uncover the gene expression status of each cell, thus allowing comprehensive assessment of intercellular heterogeneity. Because of the influence of sample size and sequencing depth, the specificity of genes in different cell types for breast cancer cannot be fully revealed. Therefore, the present study integrated two public breast cancer scRNA-seq datasets aiming to investigate the functions of different type of immune cells in tumor microenvironment. We identified total five significant differential expressed genes of B cells, T cells and macrophage and explored their functions and immune mechanisms in breast cancer. Finally, we performed functional annotation analyses using the top fifteen differentially expressed genes in each immune cell type to discover the immune-related pathways and gene ontology (GO) terms.

Integrated analysis of small RNAs, transcriptome and degradome sequencing reveal the drought stress network in Agropyron mongolicum Keng

Agropyron mongolicum (A. mongolicum) is an excellent gramineous forage with extreme drought tolerance, which lives in arid and semiarid desert areas. However, the mechanism that underlies the response of microRNAs (miRNAs) and their targets in A. mongolicum to drought stress is not well understood. In this study, we analyzed the transcriptome, small RNAome (specifically the miRNAome) and degradome to generate a comprehensive resource that focused on identifying key regulatory miRNA-target circuits under drought stress. The most extended transcript in each collection is known as the UniGene, and a total of 41,792 UniGenes and 1,104 miRNAs were identified, and 99 differentially expressed miRNAs negatively regulated 1,474 differentially expressed target genes. Among them, eight miRNAs were unique to A. mongolicum, and there were 36 target genes. A weighted gene co-expression network analysis identified five hub genes. The miRNAs of five hub genes were screened with an integration analysis of the degradome and sRNAs, such as osa-miR444a-3p.2-MADS47, bdi-miR408-5p_1ss19TA-CCX1, tae-miR9774_L-2R-1_1ss11GT-carC, ata-miR169a-3p-PAO2, and bdi-miR528-p3_2ss15TG20CA-HOX24. The functional annotations revealed that they were involved in mediating the brassinosteroid signal pathway, transporting and exchanging sodium and potassium ions and regulating the oxidation-reduction process, hydrolase activity, plant response to water deprivation, abscisic acid (ABA) and the ABA-activated signaling pathway to regulate drought stress. Five hub genes were discovered, which could play central roles in the regulation of drought-responsive genes. These results show that the combined analysis of miRNA, the transcriptome and degradation group provides a useful platform to investigate the molecular mechanism of drought resistance in A. mongolicum and could provide new insights into the genetic engineering of Poaceae crops in the future.

Single-Cell Transcriptome Integration Analysis Reveals the Correlation Between Mesenchymal Stromal Cells and Fibroblasts

Background: Mesenchymal stromal cells (MSCs) and fibroblasts show similar morphology, surface marker expression, and proliferation, differentiation, and immunomodulatory capacities. These similarities not only blur their cell identities but also limit their application. Methods: We performed single-cell transcriptome sequencing of the human umbilical cord and foreskin MSCs (HuMSCs and FSMSCs) and extracted the single-cell transcriptome data of the bone marrow and adipose MSCs (BMSCs and ADMSCs) from the Gene Expression Omnibus (GEO) database. Then, we performed quality control, batch effect correction, integration, and clustering analysis of the integrated single-cell transcriptome data from the HuMSCs, FMSCs, BMSCs, and ADMSCs. The cell subsets were annotated based on the surface marker phenotypes for the MSCs (CD105 ⁺ , CD90 ⁺, CD73 ⁺, CD45 ^-, CD34 ^-, CD19 ^-, HLA-DRA ^-, and CD11b ^-), fibroblasts (VIM ⁺, PECAM1 ^-, CD34 ^-, CD45 ^-, EPCAM ^-, and MYH11 ^-), and pericytes (CD146 ⁺, PDGFRB ⁺, PECAM1 ^-, CD34 ^-, and CD45 ^-). The expression levels of common fibroblast markers (ACTA2, FAP, PDGFRA, PDGFRB, S100A4, FN1, COL1A1, POSTN, DCN, COL1A2, FBLN2, COL1A2, DES, and CDH11) were also analyzed in all cell subsets. Finally, the gene expression profiles, differentiation status, and the enrichment status of various gene sets and regulons were compared between the cell subsets. Results: We demonstrated 15 distinct cell subsets in the integrated single-cell transcriptome sequencing data. Surface marker annotation demonstrated the MSC phenotype in 12 of the 15 cell subsets. C10 and C14 subsets demonstrated both the MSC and pericyte phenotypes. All 15 cell subsets demonstrated the fibroblast phenotype. C8, C12, and C13 subsets exclusively demonstrated the fibroblast phenotype. We identified 3,275 differentially expressed genes, 305 enriched gene sets, and 34 enriched regulons between the 15 cell subsets. The cell subsets that exclusively demonstrated the fibroblast phenotype represented less primitive and more differentiated cell types. Conclusion: Cell subsets with the MSC phenotype also demonstrated the fibroblast phenotype, but cell subsets with the fibroblast phenotype did not necessarily demonstrate the MSC phenotype, suggesting that MSCs represented a subclass of fibroblasts. We also demonstrated that the MSCs and fibroblasts represented highly heterogeneous populations with distinct cell subsets, which could be identified based on the differentially enriched gene sets and regulons that specify proliferating, differentiating, metabolic, and/or immunomodulatory functions.

Integration analysis identifies the role of metallothionein in the progression from hepatic steatosis to steatohepatitis

BACKGROUND

Non-alcoholic fatty liver disease (NAFLD), a metabolic disorder that develops from non-alcoholic fatty liver (NAFL) to non-alcoholic steatohepatitis (NASH), has become an epidemic of chronic liver dysfunction worldwide. However, mechanisms that govern the transition from NAFL to NASH have not been fully elucidated.

METHODS

Gene expression profile data of NAFLD liver tissues were obtained from Gene Expression Omnibus (GEO), including three microarray datasets with 60 NAFL and 44 NASH patients. Integrative differentially expressed genes (DEGs) between NAFL and NASH patients were identified using robust rank aggregation (RRA) analysis. Hub genes were identified combined with gene ontology functional annotation and protein-protein interaction network construction and validated using a sequencing dataset. Huh-7 cells with palmitate-induced lipid overload and NAFLD-diet mouse model of different stages were used to verify our findings.

RESULTS

RRA analysis determined 70 robust DEGs between NAFL and NASH. The most robustly upregulated genes were SPP1, AKR1B10, CHST9, and ANXA2, while the most robustly downregulated DEGs were SNORD94, SCARNA10, SNORA20, and MT1M. Cellular response to zinc ion (GO: 0071294) ranked first in GO analysis of downregulated genes, and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment showed that mineral absorption (hsa04978) was significantly enriched. The involvement of the metallothionein pathway was further validated by the decrease of Mt1 expression during NAFL to NASH progression in NAFLD mice and the protection from lipotoxicity in liver cells by overexpressing MT1M.

CONCLUSIONS

Our integrated analysis identified novel gene signatures and provided comprehensive molecular mechanisms underlying the transition from NAFL to NASH. Metallothionein might be a potential intervention target for NAFLD progression.

Integration of small RNA, degradome, and transcriptome sequencing data illustrates the mechanism of low phosphorus adaptation in Camellia oleifera

Phosphorus (P) is an indispensable macronutrient for plant growth and development, and it is involved in various cellular biological activities in plants. Camellia oleifera is a unique high-quality woody oil plant that grows in the hills and mountains of southern China. However, the available P content is deficient in southern woodland soil. Until now, few studies focused on the regulatory functions of microRNAs (miRNAs) and their target genes under low inorganic phosphate (Pi) stress. In this study, we integrated small RNA, degradome, and transcriptome sequencing data to investigate the mechanism of low Pi adaptation in C. oleifera. We identified 40,689 unigenes and 386 miRNAs by the deep sequencing technology and divided the miRNAs into four different groups. We found 32 miRNAs which were differentially expressed under low Pi treatment. A total of 414 target genes of 108 miRNAs were verified by degradome sequencing. Gene ontology (GO) functional analysis of target genes found that they were related to the signal response to the stimulus and transporter activity, indicating that they may respond to low Pi stress. The integrated analysis revealed that 31 miRNA-target pairs had negatively correlated expression patterns. A co-expression regulatory network was established based on the profiles of differentially expressed genes. In total, three hub genes (ARF22, WRKY53, and SCL6), which were the targets of differentially expressed miRNAs, were discovered. Our results showed that integrated analyses of the small RNA, degradome, and transcriptome sequencing data provided a valuable basis for investigating low Pi in C. oleifera and offer new perspectives on the mechanism of low Pi tolerance in woody oil plants.

Design and Integrated Analysis of a Flexible Support Microstructure with a Honeycomb Sandwich for the Optical Window of a Hypersonic Remote Sensor

In order to reduce the influence of the optical window on the image quality of a hypersonic visible light optical remote sensor, we propose a method of adding a double-layer semicircular honeycomb core microstructure with flexible support of a high temperature elastic alloy between a window glass and a frame to reduce the influence of complex thermal stress on the surface accuracy of the optical window. An equivalent model of a semicircular honeycomb structure was established, the elastic parameters of the semicircular honeycomb sandwich microstructure were derived by an analytical method, and a numerical verification and finite element simulation were carried out. The results show that the equivalent model is in good agreement with the detailed model. The optical-mechanical-thermal integrated simulation analysis of the optical window assembly with flexible supporting microstructure proves that the semicircular honeycomb sandwich flexible supporting structure has a positive effect on stress attenuation of the window glass and ensures the wave aberration accuracy of the transmitted optical path difference of the optical window (PV < 0.665 λ, RMS < 0.156 λ, λ = 632.8 nm). Combined with the actual optical system, the optical performance of the window assembly under the flexible support structure is verified. The simulation results show that the spatial frequency of the modulation transfer function (MTF) of the optical system after focusing is not less than 0.58 in the range of 0–63 cycle/mm and the relative decline of MTF is not more than 0.01, which meet the imaging requirements of a remote sensor. The study results show that the proposed metal-based double-layer semicircular honeycomb sandwich flexible support microstructure ensures the imaging quality of the optical window under ultra-high temperature conditions.

Analysis of DNA Methylation Profiles in Mandibular Condyle of Chicks With Crossed Beaks Using Whole-Genome Bisulfite Sequencing

Crossed beaks have been observed in at least 12 chicken strains around the world, which severely impairs their growth and welfare. To explore the intrinsic factor causing crossed beaks, this study measured the length of bilateral mandibular ramus of affected birds, and investigated the genome-wide DNA methylation profiles of normal and affected sides of mandibular condyle. Results showed that the trait was caused by impaired development of unilateral mandibular ramus, which is extended through calcification of mandibular condyle. The methylation levels in the CG contexts were higher than that of CHG and CHH, with the highest methylation level of gene body region, followed by transcription termination sites and downstream. Subsequently, we identified 1,568 differentially methylated regions and 1,317 differentially methylated genes in CG contexts. Functional annotation analysis of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes showed that these genes were involved in bone mineralization and bone morphogenesis. Furthermore, by combining the WGBS and previous RNA-Seq data, 11 overlapped genes were regulated by both long non-coding RNA and DNA methylation. Among them, FIGNL1 is an important gene in calcification of mandibular condyle. Generally, because the affected genes play key roles in maintaining mandibular calcification, these changes may be pivotal factors of crossed beaks.

Multi-omics analysis to visualize the dynamic roles of defense genes in the response of tea plants to gray blight

Gray blight (GB) is one of the most destructive diseases of tea plants, causing considerable damage and productivity losses; however, the dynamic roles of defense genes during pathogen infection remain largely unclear. To explore the numerous molecular interactions associated with GB stress in tea plants, we employed transcriptome, sRNAome and degradome sequencing from 1 to 13 days post-inoculation (dpi) at 3-day intervals. The transcriptomics results showed that differentially expressed genes (DEGs) related to flavonoid synthesis, such as chalcone synthase (CHS) and phenylalanine ammonia-lyase (PAL), were particularly induced at 4 dpi. Consistent with this, the contents of catechins (especially gallocatechin), which are the dominant flavonoids in tea plants, also increased in the leaves of tea plants infected with GB. Combined analysis of the sRNAome and degradome revealed that microRNAs could mediate tea plant immunity by regulating DEG expression at the post-transcriptional level. Co-expression network analysis demonstrated that miR530b-ethylene responsive factor 96 (ERF96) and miRn211-thaumatin-like protein (TLP) play crucial roles in the response to GB. Accordingly, gene-specific antisense oligonucleotide assays suggested that suppressing ERF96 decreased the levels of reactive oxygen species (ROS), whereas suppressing TLP increased the levels of ROS. Furthermore, ERF96 was induced, but TLP was suppressed, in susceptible tea cultivars. Our results collectively demonstrate that ERF96 is a negative regulator and TLP is a positive regulator in the response of tea plants to GB. Taken together, our comprehensive integrated analysis reveals a dynamic regulatory network linked to GB stress in tea plants and provides candidate genes for improvement of tea plants.

Integrated microRNA and mRNA Expression Profiling Identifies Novel Targets and Networks Associated with Ebstein's Anomaly

Little is known about abundance level changes of circulating microRNAs (miRNAs) and messenger RNAs (mRNA) in patients with Ebstein’s anomaly (EA). Here, we performed an integrated analysis to identify the differentially abundant miRNAs and mRNA targets and to identify the potential therapeutic targets that might be involved in the mechanisms underlying EA. A large panel of human miRNA and mRNA microarrays were conducted to determine the genome-wide expression profiles in the blood of 16 EA patients and 16 age and gender-matched healthy control volunteers (HVs). Differential abundance level of single miRNA and mRNA was validated by Real-Time quantitative PCR (RT-qPCR). Enrichment analyses of altered miRNA and mRNA abundance levels were identified using bioinformatics tools. Altered miRNA and mRNA abundance levels were observed between EA patients and HVs. Among the deregulated miRNAs and mRNAs, 76 miRNAs (49 lower abundance and 27 higher abundance, fold-change of ≥2) and 29 mRNAs (25 higher abundance and 4 lower abundance, fold-change of ≥1.5) were identified in EA patients compared to HVs. Bioinformatics analysis identified 37 pairs of putative miRNA-mRNA interactions. The majority of the correlations were detected between the lower abundance level of miRNA and higher abundance level of mRNA, except for let-7b-5p, which showed a higher abundance level and their target gene, SCRN3, showed a lower abundance level. Pathway enrichment analysis of the deregulated mRNAs identified 35 significant pathways that are mostly involved in signal transduction and cellular interaction pathways. Our findings provide new insights into a potential molecular biomarker(s) for the EA that may guide the development of novel targeting therapies.

Integrated Analysis of Key Genes and Pathways Involved in Fetal Growth Restriction and Their Associations With the Dysregulation of the Maternal Immune System

Fetal growth restriction (FGR) is a common pregnancy complication and a risk factor for infant death. Most patients with FGR have preeclampsia, gestational diabetes mellitus, or other etiologies, making it difficult to determine the specific molecular mechanisms underlying FGR. In this study, an integrated analysis was performed using gene expression profiles obtained from Gene Expression Omnibus. Differentially expressed genes (DEGs) between healthy and FGR groups were screened and evaluated by functional enrichment and network analyses. In total, 80 common DEGs (FDR < 0.05) and 17 significant DEGs (FDR < 0.005) were screened. These genes were enriched for functions in immune system dysregulation in the placenta based on Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses. Among hub genes identified as candidates for FGR and fetal reprogramming, LEP, GBP5, HLA–DQA1, and CTGF were checked by quantitative polymerase chain reaction, immunohistochemistry, and western blot assays in placental tissues. Immune imbalance could cause hypoxia environment in placenta tissues, thus regulating the fetal-reprogramming. A significant association between CTGF and HIF-1α levels was confirmed in placenta tissues and HTR8 cells under hypoxia. Our results suggest that an immune imbalance in the placenta causes FGR without other complications. We provide the first evidence for roles of CTGF in FGR and show that CTGF may function via HIF-1α-related pathways. Our findings elucidate the pathogenesis of FGR and provide new therapeutic targets.

The Integrated Landscape of Biological Candidate Causal Genes in Coronary Artery Disease

Background

Genome-wide association studies (GWASs) have identified more than 150 genetic loci that demonstrate robust association with coronary artery disease (CAD). In contrast to the success of GWAS, the translation from statistical signals to biological mechanism and exploration of causal genes for drug development remain difficult, owing to the complexity of gene regulatory and linkage disequilibrium patterns. We aim to prioritize the plausible causal genes for CAD at a genome-wide level.

Methods

We integrated the latest GWAS summary statistics with other omics data from different layers and utilized eight different computational methods to predict CAD potential causal genes. The prioritized candidate genes were further characterized by pathway enrichment analysis, tissue-specific expression analysis, and pathway crosstalk analysis.

Results

Our analysis identified 55 high-confidence causal genes for CAD, among which 15 genes (LPL, COL4A2, PLG, CDKN2B, COL4A1, FES, FLT1, FN1, IL6R, LPA, PCSK9, PSRC1, SMAD3, SWAP70, and VAMP8) ranked the highest priority because of consistent evidence from different data-driven approaches. GO analysis showed that these plausible causal genes were enriched in lipid metabolic and extracellular regions. Tissue-specific enrichment analysis revealed that these genes were significantly overexpressed in adipose and liver tissues. Further, KEGG and crosstalk analysis also revealed several key pathways involved in the pathogenesis of CAD.

Conclusion

Our study delineated the landscape of CAD potential causal genes and highlighted several biological processes involved in CAD pathogenesis. Further studies and experimental validations of these genes may shed light on mechanistic insights into CAD development and provide potential drug targets for future therapeutics.

Adaptation of hepatitis C virus to interferon lambda polymorphism across multiple viral genotypes

Genetic polymorphism in the interferon lambda (IFN-λ) region is associated with spontaneous clearance of hepatitis C virus (HCV) infection and response to interferon-based treatment. Here, we evaluate associations between IFN-λ polymorphism and HCV variation in 8729 patients (Europeans 77%, Asians 13%, Africans 8%) infected with various viral genotypes, predominantly 1a (41%), 1b (22%) and 3a (21%). We searched for associations between rs12979860 genotype and variants in the NS3, NS4A, NS5A and NS5B HCV proteins. We report multiple associations in all tested proteins, including in the interferon-sensitivity determining region of NS5A. We also assessed the combined impact of human and HCV variation on pretreatment viral load and report amino acids associated with both IFN-λ polymorphism and HCV load across multiple viral genotypes. By demonstrating that IFN-λ variation leaves a large footprint on the viral proteome, we provide evidence of pervasive viral adaptation to innate immune pressure during chronic HCV infection.

HisCoM-mimi: Software for Hierarchical Structural Component Analysis for miRNA-mRNA Integration Model for Binary Phenotypes

To identify miRNA-mRNA interaction pairs associated with binary phenotypes, we propose a hierarchical structural component model for miRNA-mRNA integration (HisCoM-mimi). Information on known mRNA targets provided by TargetScan is used to perform HisCoM-mimi. However, multiple databases can be used to find miRNA-mRNA signatures with known biological information through different algorithms. To take these additional databases into account, we present our advanced application software for HisCoM-mimi for binary phenotypes. The proposed HisCoM-mimi supports both TargetScan and miRTarBase, which provides manually-verified information initially gathered by text-mining the literature. By integrating information from miRTarBase into HisCoM-mimi, a broad range of target information derived from the research literature can be analyzed. Another improvement of the new HisCoM-mimi approach is the inclusion of updated algorithms to provide the lasso and elastic-net penalties for users who want to fit a model with a smaller number of selected miRNAs and mRNAs. We expect that our HisCoM-mimi software will make advanced methods accessible to researchers who want to identify miRNA-mRNA interaction pairs related with binary phenotypes.

Liver Transcriptome and miRNA Analysis of Silver Carp (Hypophthalmichthys molitrix) Intraperitoneally Injected With Microcystin-LR

Next-generation sequencing was used to analyze the effects of toxic microcystin-LR (MC-LR) on silver carp (Hypophthalmichthys molitrix). Silver carps were intraperitoneally injected with MC-LR, and RNA-seq and miRNA-seq in the liver were analyzed at 0.25, 0.5, and 1 h. The expression of glutathione S-transferase (GST), which acts as a marker gene for MC-LR, was tested to determine the earliest time point at which GST transcription was initiated in the liver tissues of the MC-LR-treated silver carps. Hepatic RNA-seq/miRNA-seq analysis and data integration analysis were conducted with reference to the identified time point. Quantitative PCR (qPCR) was performed to detect the expression of the following genes at the three time points: heme oxygenase 1 (HO-1), interleukin-10 receptor 1 (IL-10R1), apolipoprotein A-I (apoA-I), and heme binding protein 2 (HBP2). Results showed that the liver GST expression was remarkably decreased at 0.25 h (P < 0.05). RNA-seq at this time point revealed that the liver tissue contained 97,505 unigenes, including 184 significantly different unigenes and 75 unknown genes. Gene Ontology (GO) term enrichment analysis suggested that 35 of the 145 enriched GO terms were significantly enriched and mainly related to the immune system regulation network. KEGG pathway enrichment analysis showed that 18 of the 189 pathways were significantly enriched, and the most significant was a ribosome pathway containing 77 differentially expressed genes. miRNA-seq analysis indicated that the longest miRNA had 22 nucleotides (nt), followed by 21 and 23 nt. A total of 286 known miRNAs, 332 known miRNA precursor sequences, and 438 new miRNAs were predicted. A total of 1,048,575 mRNA–miRNA interaction sites were obtained, and 21,252 and 21,241 target genes were respectively predicted in known and new miRNAs. qPCR revealed that HO-1, IL-10R1, apoA-I, and HBP2 were significantly differentially expressed and might play important roles in the toxicity and liver detoxification of MC-LR in fish. These results were consistent with those of high-throughput sequencing, thereby verifying the accuracy of our sequencing data. RNA-seq and miRNA-seq analyses of silver carp liver injected with MC-LR provided valuable and new insights into the toxic effects of MC-LR and the antitoxic mechanisms of MC-LR in fish.

The RNA/miRNA data are available from the NCBI database Registration No. : SRP075165.

Development of the First World Health Organization Lentiviral Vector Standard: Toward the Production Control and Standardization of Lentivirus-Based Gene Therapy Products

Gene therapy is a rapidly evolving field. So far, there have been >2,400 gene therapy products in clinical trials and four products on the market. A prerequisite for producing gene therapy products is ensuring their quality and safety. This requires appropriately controlled and standardized production and testing procedures that result in consistent safety and efficacy. Assuring the quality and safety of lentivirus-based gene therapy products in particular presents a great challenge because they are cell-based multigene products that include viral and therapeutic proteins as well as modified cells. In addition to the continuous refinement of a product, changes in production sites and manufacturing processes have become more and more common, posing challenges to developers regarding reproducibility and comparability of results. This paper discusses the concept of developing a first World Health Organization International Standard, suitable for the standardization of assays and enabling comparison of cross-trial and cross-manufacturing results for this important vector platform. The standard will be expected to optimize the development of gene therapy medicinal products, which is especially important, given the usually orphan nature of the diseases to be treated, naturally hampering reproducibility and comparability of results.

Identify signature regulatory network for glioblastoma prognosis by integrative mRNA and miRNA co-expression analysis

Glioblastoma multiforme (GBM) is the most common and aggressive type of primary brain tumor in adults. Patients with this disease have a poor prognosis. The objective of this study is to identify survival-related individual genes (or miRNAs) and miRNA -mRNA pairs in GBM using a multi-step approach. First, the weighted gene co-expression network analysis and survival analysis are applied to identify survival-related modules from mRNA and miRNA expression profiles, respectively. Subsequently, the role of individual genes (or miRNAs) within these modules in GBM prognosis are highlighted using survival analysis. Finally, the integration analysis of miRNA and mRNA expression as well as miRNA target prediction is used to identify survival-related miRNA -mRNA regulatory network. In this study, five genes and two miRNA modules that significantly correlated to patient's survival. In addition, many individual genes (or miRNAs) assigned to these modules were found to be closely linked with survival. For instance, increased expression of neuropilin-1 gene (a member of module turquoise) indicated poor prognosis for patients and a group of miRNA -mRNA regulatory networks that comprised 38 survival-related miRNA -mRNA pairs. These findings provide a new insight into the underlying molecular regulatory mechanisms of GBM.

Integration of small RNAs, degradome and transcriptome sequencing in hyperaccumulator Sedum alfredii uncovers a complex regulatory network and provides insights into cadmium phytoremediation

The hyperaccumulating ecotype of Sedum alfredii Hance is a cadmium (Cd)/zinc/lead co-hyperaccumulating species of Crassulaceae. It is a promising phytoremediation candidate accumulating substantial heavy metal ions without obvious signs of poisoning. However, few studies have focused on the regulatory roles of miRNAs and their targets in the hyperaccumulating ecotype of S. alfredii. Here, we combined analyses of the transcriptomics, sRNAs and the degradome to generate a comprehensive resource focused on identifying key regulatory miRNA-target circuits under Cd stress. A total of 87 721 unigenes and 356 miRNAs were identified by deep sequencing, and 79 miRNAs were differentially expressed under Cd stress. Furthermore, 754 target genes of 194 miRNAs were validated by degradome sequencing. A gene ontology (GO) enrichment analysis of differential miRNA targets revealed that auxin, redox-related secondary metabolism and metal transport pathways responded to Cd stress. An integrated analysis uncovered 39 pairs of miRNA targets that displayed negatively correlated expression profiles. Ten miRNA-target pairs also exhibited negative correlations according to a real-time quantitative PCR analysis. Moreover, a coexpression regulatory network was constructed based on profiles of differentially expressed genes. Two hub genes, ARF4 (auxin response factor 4) and AAP3 (amino acid permease 3), which might play central roles in the regulation of Cd-responsive genes, were uncovered. These results suggest that comprehensive analyses of the transcriptomics, sRNAs and the degradome provided a useful platform for investigating Cd hyperaccumulation in S. alfredii, and may provide new insights into the genetic engineering of phytoremediation.

Key tumor suppressor genes inactivated by "greater promoter" methylation and somatic mutations in head and neck cancer

Tumor suppressor genes (TSGs) are commonly inactivated by somatic mutation and/or promoter methylation; yet, recent high-throughput genomic studies have not identified key TSGs inactivated by both mechanisms. We pursued an integrated molecular analysis based on methylation binding domain sequencing (MBD-seq), 450K Methylation arrays, whole exome sequencing, and whole genome gene expression arrays in primary head and neck squamous cell carcinoma (HNSCC) tumors and matched uvulopalatopharyngoplasty tissue samples (UPPPs). We uncovered 186 downregulated genes harboring cancer specific promoter methylation including PAX1 and PAX5 and we identified 10 key tumor suppressor genes (GABRB3, HOXC12, PARP15, SLCO4C1, CDKN2A, PAX1, PIK3AP1, HOXC6, PLCB1, and ZIC4) inactivated by both promoter methylation and/or somatic mutation. Among the novel tumor suppressor genes discovered with dual mechanisms of inactivation, we found a high frequency of genomic and epigenomic alterations in the PAX gene family of transcription factors, which selectively impact canonical NOTCH and TP53 pathways to determine cell fate, cell survival, and genome maintenance. Our results highlight the importance of assessing TSGs at the genomic and epigenomic level to identify key pathways in HNSCC, deregulated by simultaneous promoter methylation and somatic mutations.

Development of a combined real time monitoring and integration analysis system for volatile organic compounds (VOCs)

A combined integration analysis and real time monitoring (Peak Capture System) system was developed for volatile organic compounds (VOCs). Individual integration analysis and real time monitoring can be used to qualitatively and quantitatively analyze VOCs in the atmosphere and in indoor environments and determine the variation in total VOC (TVOC) concentration with time, respectively. In the Peak Capture System, real time monitoring was used to predict future elevations in the TVOC concentration (peak), and this was used an indicator of when to collect (capture) ambient air samples for integration analysis. This enabled qualitative and quantitative analysis of VOCs when the TVOC concentration was high. We developed an algorithm to predict variation in the TVOC concentration, and constructed an automatic system to initiate air sampling for integration analysis. With the system, auto-sampling and analysis of VOCs in a conventional house were conducted. In comparison with background concentrations, the results of peak analysis enabled identification of compounds whose concentration rose. This also enabled an evaluation of possible VOC emission sources.