Cortical thickness differences are associated with cellular component morphogenesis of astrocytes and excitatory neurons in nonsuicidal self-injuring youth.

Nonsuicidal self-injury (NSSI) generally occurs in youth and probably progresses to suicide. An examination of cortical thickness differences (ΔCT) between NSSI individuals and controls is crucial to investigate potential neurobiological correlates. Notably, ΔCT are influenced by specific genetic factors, and a large proportion of cortical thinning is associated with the expression of genes that overlap in astrocytes and pyramidal cells. However, in NSSI youth, the mechanisms underlying the relations between the genetic and cell type-specific transcriptional signatures to ΔCT are unclear. Here, we studied the genetic association of ΔCT in NSSI youth by performing a partial least-squares regression (PLSR) analysis of gene expression data and 3D-T1 brain images of 45 NSSI youth and 75 controls. We extracted the top-10 Gene Ontology terms for the enrichment results of upregulated PLS component 1 genes related to ΔCT to conduct the cell-type classification and enrichment analysis. Enrichment of cell type-specific genes shows that cellular component morphogenesis of astrocytes and excitatory neurons accounts for the observed NSSI-specific ΔCT. We validated the main results in independent datasets to verify the robustness and specificity. We concluded that the brain ΔCT is associated with cellular component morphogenesis of astrocytes and excitatory neurons in NSSI youth.

Mask blast with a new chemical logic of amino acids for improved protein function prediction.

With the exponential increase in protein sequence data, there is an urgency to acquire a knowledge of function of the millions of sequences, using automated methods with high reliability. Conventional methods for annotating a protein sequence transfer the function of a homologous sequence with known functions based on evolutionary information. Here, we present a newer way of classifying amino acids based on chemical measures and demonstrate that, when integrated with mask BLAST, the chemical properties identified outperform current classifications of amino acids as well as evolutionary measures in function detection.

CellNetVis: a web tool for visualization of biological networks using force-directed layout constrained by cellular components.

BACKGROUND: The advent of "omics" science has brought new perspectives in contemporary biology through the high-throughput analyses of molecular interactions, providing new clues in protein/gene function and in the organization of biological pathways. Biomolecular interaction networks, or graphs, are simple abstract representations where the components of a cell (e.g. proteins, metabolites etc.) are represented by nodes and their interactions are represented by edges. An appropriate visualization of data is crucial for understanding such networks, since pathways are related to functions that occur in specific regions of the cell. The force-directed layout is an important and widely used technique to draw networks according to their topologies. Placing the networks into cellular compartments helps to quickly identify where network elements are located and, more specifically, concentrated. Currently, only a few tools provide the capability of visually organizing networks by cellular compartments. Most of them cannot handle large and dense networks. Even for small networks with hundreds of nodes the available tools are not able to reposition the network while the user is interacting, limiting the visual exploration capability. RESULTS: Here we propose CellNetVis, a web tool to easily display biological networks in a cell diagram employing a constrained force-directed layout algorithm. The tool is freely available and open-source. It was originally designed for networks generated by the Integrated Interactome System and can be used with networks from others databases, like InnateDB. CONCLUSIONS: CellNetVis has demonstrated to be applicable for dynamic investigation of complex networks over a consistent representation of a cell on the Web, with capabilities not matched elsewhere.

Extent of agreement between the body fluid model of Sysmex XN-20 and the manual microscopy method.

BACKGROUND: Although the correlations concerning cellular component analysis between the Sysmex XN-20 body fluid (BF) model and manual microscopy have been investigated by several studies, the extent of agreement between these two methods has not been investigated. METHODS: A total of 90 BF samples were prospectively collected and analyzed using the Sysmex XN-20 BF model and microscopy. The extent of agreement between these two methods was evaluated using the Bland-Altman approach. Receiver operating characteristic (ROC) curve analysis was employed to evaluate the diagnostic accuracy of high-fluorescence (HF) BF cells for malignant diseases. RESULTS: The agreements of white blood cell (WBC), red blood cell (RBC), and percentages of neutrophils, lymphocytes, and monocytes between the Sysmex XN-20 BF model and manual microscopy were imperfect. The areas under the ROC curves for absolute and relative HF cells were 0.67 (95% confidence interval [CI]: 0.56-0.78) and 0.60 (95% CI: 0.48-0.72), respectively. CONCLUSION: Due to the Sysmex XN-20 BF model's imperfect agreement with manual microscopy and its weak diagnostic accuracy for malignant diseases, the current evidence does not support replacing manual microscopy with this model in clinical practice.

Combined exposure of PVC-microplastic and mercury chloride (HgCl2) in sorghum (Pennisetum glaucum L.) when its seeds are primed titanium dioxide nanoparticles (TiO2-NPs).

The present work studied the impact of different levels of PVC-microplastics (PVC-MPs), namely 0 (no PVC-MPs), 2, and 4 mg L-1, along with mercury (Hg) levels of 0 (no Hg), 10, and 25 mg kg-1 in the soil, while concurrently applying titanium dioxide-nanoparticles (TiO2-NPs) at 0 (no TiO2-NPs), 50, and 100 µg mL-1 to sorghum (Pennisetum glaucum L.) plants. This study aimed to examine plant growth and biomass, photosynthetic pigments and gas exchange characteristics, oxidative stress indicators, and the response of various antioxidants (enzymatic and non-enzymatic) and their specific gene expression, proline metabolism, the AsA-GSH cycle, and cellular fractionation in the plants. The research outcomes indicated that elevated levels of PVC-MPs and Hg stress in the soil notably reduced plant growth and biomass, photosynthetic pigments, and gas exchange attributes. However, PVC-MPs and Hg stress also induced oxidative stress in the roots and shoots of the plants by increasing malondialdehyde (MDA), hydrogen peroxide (H2O2), and electrolyte leakage (EL) which also induced increased compounds of various enzymatic and non-enzymatic antioxidants and also the gene expression and sugar content. Furthermore, a significant increase in proline metabolism, the AsA-GSH cycle, and the pigmentation of cellular components was observed. Although, the application of TiO2-NPs showed a significant increase in plant growth and biomass, gas exchange characteristics, enzymatic and non-enzymatic compounds, and their gene expression and also decreased oxidative stress. In addition, the application of TiO2-NPs enhanced cellular fractionation and decreased the proline metabolism and AsA-GSH cycle in P. glaucum plants. These results open new insights for sustainable agriculture practices and hold immense promise in addressing the pressing challenges of heavy metal contamination in agricultural soils.

Composition of Proteins Associated with Red Clover (Trifolium pratense) and the Microbiota Identified in Honey.

The nutritional composition of honey is determined by environmental conditions, and botanical and geographical origin. In addition to carbohydrates, honey also contain pollen grains, proteins, free amino acids, and minerals. Although the content of proteins in honey is low, they are an important component that confirms the authenticity and quality of honey; therefore, they became a popular study object. The aim of the study was to evaluate protein content and composition of monofloral red clover and rapeseed honey collected from five different districts of Lithuania. Forty-eight proteins were identified in five different origin honey samples by liquid chromatography. The number of red clover proteins identified in individual honey samples in monofloral red clover honey C3 was 39 in polyfloral honey S22-36, while in monofloral rapeseed honey S5, S15, and S23 there was 33, 32, and 40 respectively. Aphids' proteins and lactic acid bacteria were identified in all honey samples tested. The linear relationship and the strongest correlation coefficient (r = 0.97) were determined between the content of Apilactobacillus kunkeei and Apilactobacillus apinorum, as well as between the number of faba bean (Vicia faba) pollen and lactic acid bacteria (r = 0.943). The data show a strong correlation coefficient between the amount of lactic acid and aphid protein number (r = 0.693). More studies are needed to evaluate the relationship between the pollination efficiency of red clover by bees and the multiplicity of red clover proteins in honey protein, as well as microbiota diversity and the influence of nature or plant diversity on the occurrence of microbiota in honey.

Peripheral Blood Gene Expression Profile of Infants with Atopic Dermatitis.

To enhance the understanding of molecular mechanisms and mine previously unidentified biomarkers of pediatric atopic dermatitis, PBMC gene expression profiles were generated by RNA sequencing in infants with atopic dermatitis and age-matched controls. A total of 178 significantly differentially expressed genes (DEGs) (115 upregulations and 63 downregulations) were seen, compared with those in healthy controls. The DEGs identified included IL1ß, TNF, TREM1, IL18R1, and IL18RAP. DEGs were validated by real-time RT- qPCR in a larger number of samples from PBMCs of infants with atopic dermatitis aged <12 months. Using the DAVID (Database for Annotation, Visualization and Integrated Discovery) database, functional and pathway enrichment analyses of DEGs were performed. Gene ontology enrichment analysis showed that DEGs were associated with immune responses, inflammatory responses, regulation of immune responses, and platelet activation. Pathway analysis indicated that DEGs were enriched in cytokine‒cytokine receptor interaction, immunoregulatory interactions between lymphoid and nonlymphoid cells, hematopoietic cell lineage, phosphoinositide 3-kinase‒protein kinase B signaling pathway, NK cell‒mediated cytotoxicity, and platelet activation. Furthermore, the protein‒protein interaction network was predicted using the STRING (Search Tool for the Retrieval of Interacting Genes/Proteins) database and visualized with Cytoscape software. Finally, on the basis of the protein‒protein interaction network, 18 hub genes were selected, and two significant modules were obtained. In conclusion, this study sheds light on the molecular mechanisms of pediatric atopic dermatitis and may provide diagnostic biomarkers and therapeutic targets.

Gene and protein expression profiles of olfactory ensheathing cells from olfactory bulb versus olfactory mucosa.

Olfactory ensheathing cells (OECs) from the olfactory bulb (OB) and the olfactory mucosa (OM) have the capacity to repair nerve injury. However, the difference in the therapeutic effect between OB-derived OECs and OM-derived OECs remains unclear. In this study, we extracted OECs from OB and OM and compared the gene and protein expression profiles of the cells using transcriptomics and non-quantitative proteomics techniques. The results revealed that both OB-derived OECs and OM-derived OECs highly expressed genes and proteins that regulate cell growth, proliferation, apoptosis and vascular endothelial cell regeneration. The differentially expressed genes and proteins of OB-derived OECs play a key role in regulation of nerve regeneration and axon regeneration and extension, transmission of nerve impulses and response to axon injury. The differentially expressed genes and proteins of OM-derived OECs mainly participate in the positive regulation of inflammatory response, defense response, cytokine binding, cell migration and wound healing. These findings suggest that differentially expressed genes and proteins may explain why OB-derived OECs and OM-derived OECs exhibit different therapeutic roles. This study was approved by the Animal Ethics Committee of the General Hospital of Ningxia Medical University (approval No. 2017-073) on February 13, 2017.

Identification of prognostic biomarkers for breast cancer brain metastases based on the bioinformatics analysis.

PURPOSE: The prognosis of breast cancer (BC) patients who develop into brain metastases (BMs) is very poor. Thus, it is of great significance to explore the etiology of BMs in BC and identify the key genes involved in this process to improve the survival of BC patients with BMs. PATIENTS AND METHODS: The gene expression data and the clinical information of BC patients were downloaded from TCGA and GEO database. Differentially expressed genes (DEGs) in TCGA-BRCA and GSE12276 were overlapped to find differentially expressed metastatic genes (DEMGs). The protein-protein interaction (PPI) network of DEMGs was constructed via STRING database. ClusterProfiler R package was applied to perform the gene ontology (GO) enrichment analysis of DEMGs. The univariate Cox regression analysis and the Kaplan-Meier (K-M) curves were plotted to screen DEMGs associated with the overall survival and the metastatic recurrence survival, which were identified as the key genes associated with the BMs in BC. The immune infiltration and the expressions of immune checkpoints for BC patients with brain relapses and BC patients with other relapses were analyzed respectively. The correlations among the expressions of key genes and the differently infiltrated immune cells or the differentially expressed immune checkpoints were calculated. The gene set enrichment analysis (GSEA) of each key gene was conducted to investigate the potential mechanisms of key genes involved in BC patients with BMs. Moreover, CTD database was used to predict the drug-gene interaction network of key genes. RESULTS: A total of 154 DEGs were identified in BC patients at M0 and M1 in TCGA database. A total of 667 DEGs were identified in BC patients with brain relapses and with other relapses. By overlapping these DEGs, 17 DEMGs were identified, which were enriched in the cell proliferation related biological processes and the immune related molecular functions. The univariate Cox regression analysis and the Kaplan-Meier curves revealed that CXCL9 and GPR171 were closely associated with the overall survival and the metastatic recurrence survival and were identified as key genes associated with BMs in BC. The analyses of immune infiltration and immune checkpoint expressions showed that there was a significant difference of the immune microenvironment between brain relapses and other relapses in BC. GSEA indicated that CXCL9 and GPR171 may regulate BMs in BC via the immune-related pathways. CONCLUSION: Our study identified the key genes associated with BMs in BC patients and explore the underlying mechanisms involved in the etiology of BMs in BC. These findings may provide a promising approach for the treatments of BC patients with BMs.

Using bioinformatics and systems biology to discover common pathogenetic processes between sarcoidosis and COVID-19.

The coronavirus disease (COVID-19) pandemic caused by SARS-CoV-2 is ongoing. Individuals with sarcoidosis tend to develop severe COVID-19; however, the underlying pathological mechanisms remain elusive. To determine common transcriptional signatures and pathways between sarcoidosis and COVID-19, we investigated the whole-genome transcriptome of peripheral blood mononuclear cells (PBMCs) from patients with COVID-19 and sarcoidosis and conducted bioinformatic analysis, including gene ontology and pathway enrichment, protein-protein interaction (PPI) network, and gene regulatory network (GRN) construction. We identified 33 abnormally expressed genes that were common between COVID-19 and sarcoidosis. Functional enrichment analysis showed that these differentially expressed genes were associated with cytokine production involved in the immune response and T cell cytokine production. We identified several hub genes from the PPI network encoded by the common genes. These hub genes have high diagnostic potential for COVID-19 and sarcoidosis and can be potential biomarkers. Moreover, GRN analysis identified important microRNAs and transcription factors that regulate the common genes. This study provides a novel characterization of the transcriptional signatures and biological processes commonly dysregulated in sarcoidosis and COVID-19 and identified several critical regulators and biomarkers. This study highlights a potential pathological association between COVID-19 and sarcoidosis, establishing a theoretical basis for future clinical trials.

Effects of galactosyltransferase on EPS biosynthesis and freeze-drying resistance of Lactobacillus acidophilus NCFM.

Galactosyltransferase (GalT) is an important enzyme in synthesizing exopolysaccharide (EPS), the major polymer of biofilms protecting cells from severe conditions. However, the contribution to, and regulatory mechanism of GalT, in stressor resistance are still unclear. Herein, we successfully overexpressed GalT in Lactobacillus acidophilus NCFM by genetic engineering. The GalT activity and freeze-drying survival rate of the recombinant strain were significantly enhanced. The EPS yield also increased by 17.8%, indicating a positive relationship between freeze-drying resistance and EPS. RNA-Seq revealed that GalT could regulate the flux of the membrane transport system, pivotal sugar-related metabolic pathways, and promote quorum sensing to facilitate EPS biosynthesis, which enhanced freeze-drying resistance. The findings concretely prove that the mechanism of GalT regulating EPS biosynthesis plays an important role in protecting lactic acid bacteria from freeze-drying stress.

Comprehensive analysis of gene expression profiles to identify differential prognostic factors of primary and metastatic breast cancer.

Breast cancer accounts for nearly half of all cancer-related deaths in women worldwide. However, the molecular mechanisms that lead to tumour development and progression remain poorly understood and there is a need to identify candidate genes associated with primary and metastatic breast cancer progression and prognosis. In this study, candidate genes associated with prognosis of primary and metastatic breast cancer were explored through a novel bioinformatics approach. Primary and metastatic breast cancer tissues and adjacent normal breast tissues were evaluated to identify biomarkers characteristic of primary and metastatic breast cancer. The Cancer Genome Atlas-breast invasive carcinoma (TCGA-BRCA) dataset (ID: HS-01619) was downloaded using the mRNASeq platform. Genevestigator 8.3.2 was used to analyse TCGA-BRCA gene expression profiles between the sample groups and identify the differentially-expressed genes (DEGs) in each group. For each group, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were used to determine the function of DEGs. Networks of protein-protein interactions were constructed to identify the top hub genes with the highest degree of interaction. Additionally, the top hub genes were validated based on overall survival and immunohistochemistry using The Human Protein Atlas. Of the top 20 hub genes identified, four (KRT14, KIT, RAD51, and TTK) were considered as prognostic risk factors based on overall survival. KRT14 and KIT expression levels were upregulated while those of RAD51 and TTK were downregulated in patients with breast cancer. The four proposed candidate hub genes might aid in further understanding the molecular changes that distinguish primary breast tumours from metastatic tumours as well as help in developing novel therapeutics. Furthermore, they may serve as effective prognostic risk markers based on the strong correlation between their expression and patient overall survival.

Exploring the zinc-related transcriptional landscape in Alzheimer's disease.

Alzheimer's disease (AD) is a progressive neurological disorder, and increasing evidence suggests AD pathology is driven by metabolic dysfunction in the brain. Zinc is the second most abundant trace element found in the human body and is required by all living organisms. Zinc is used extensively in many biological processes, and alterations in zinc levels are implicated in the pathogenesis of numerous diseases, including AD. Since small fluctuations in brain zinc levels appear to effect AD progression, we investigated the zinc-related transcriptional responses in an AD versus non-AD state using microarray and RNA-sequencing (RNA-seq) datasets from cultured cells, mice, and humans. We identified 582 zinc-related differentially expressed genes (DEG) in human dorsolateral prefrontal cortex samples of late-onset AD (LOAD) versus non-AD controls, 146 zinc-related DEG in 5XFAD versus wild-type mice, and 95 zinc-related DEG in lipopolysaccharide (LPS)-stimulated N9 microglia versus unstimulated control cells, with 19 zinc-related DEG common to all three datasets. Of the 19 common DEG, functional enrichment and network analyses identified several biological processes and molecular functions, such as mRNA destabilization and nucleic acid binding, which may be important in neuroinflammation and AD development. Furthermore, therapeutic drugs targeting zinc-related DEG in the human dataset were identified. Taken together, these data provide insights into zinc utilization for gene transcription during AD progression which may further our understanding of AD pathogenesis and could identify new targets for therapeutic strategies targeted towards AD.

Proteome-wide prediction and analysis of the Cryptosporidium parvum protein-protein interaction network through integrative methods.

As one of the most studied Apicomplexan parasite Cryptosporidium, Cryptosporidium parvum (C. parvum) causes worldwide serious diarrhea disease cryptosporidiosis, which can be deadly to immunodeficiency individuals, newly born children, and animals. Proteome-wide identification of protein-protein interactions (PPIs) has proven valuable in the systematic understanding of the genome-phenome relationship. However, the PPIs of C. parvum are largely unknown because of the limited experimental studies carried out. Therefore, we took full advantage of three bioinformatics methods, i.e., interolog mapping (IM), domain-domain interaction (DDI)-based inference, and machine learning (ML) method, to jointly predict PPIs of C. parvum. Due to the lack of experimental PPIs of C. parvum, we used the PPI data of Plasmodium falciparum (P. falciparum), which owned the largest number of PPIs in Apicomplexa, to train an ML model to infer C. parvum PPIs. We utilized consistent results of these three methods as the predicted high-confidence PPI network, which contains 4,578 PPIs covering 554 proteins. To further explore the biological significance of the constructed PPI network, we also conducted essential network and protein functional analysis, mainly focusing on hub proteins and functional modules. We anticipate the constructed PPI network can become an important data resource to accelerate the functional genomics studies of C. parvum as well as offer new hints to the target discovery in developing drugs/vaccines.

Sustained release of naringin from silk-fibroin-nanohydroxyapatite scaffold for the enhancement of bone regeneration.

Bone defects are a common challenge in the clinical setting. Bone tissue engineering (BTE) is an effective treatment for the clinical problem of large bone defects. In this study, we fabricated silk fibroin (SF)/hydroxyapatite (HAp) scaffolds inlaid with naringin poly lactic-co-glycolic acid (PLGA) microspheres, investigating the feasibility of their application in BTE. Naringin PLGA microspheres were manufactured and adhered to the SF/HAp scaffold. Bone mesenchymal stem cells (BMSCs) were inoculated onto the SF/HAp scaffold containing naringin PLGA microsphere to examine the biocompatibility of the SF/HAp scaffolds. A rabbit femoral distal bone defect model was used to evaluate the in vivo function of the SF/HAp scaffolds containing naringin-loaded PLGA microspheres. The current study demonstrated that SF/HAp scaffolds containing naringin-loaded PLGA microspheres show promise as osteo-modulatory biomaterials for bone regeneration.

Research on the mechanism of berberine in the treatment of COVID-19 pneumonia pulmonary fibrosis using network pharmacology and molecular docking.

Purpose Pulmonary fibrosis caused by COVID-19 pneumonia is a serious complication of COVID-19 infection, there is a lack of effective treatment methods clinically. This article explored the mechanism of action of berberine in the treatment of COVID-19 (Corona Virus Disease 2019, COVID-19) pneumonia pulmonary fibrosis with the help of the network pharmacology and molecular docking. Methods We predicted the role of berberine protein targets with the Pharmmapper database and the 3D structure of berberine in the Pubchem database. And GeneCards database was used in order to search disease target genes and screen common target genes. Then we used STRING web to construct PPI interaction network of common target protein. The common target genes were analyzed by GO and KEGG by DAVID database. The disease-core target gene-drug network was established and molecular docking was used for prediction. We also analyzed the binding free energy and simulates molecular dynamics of complexes. Results Berberine had 250 gene targets, COVID-19 pneumonia pulmonary fibrosis had 191 gene targets, the intersection of which was 23 in common gene targets. Molecular docking showed that berberine was associated with CCl2, IL-6, STAT3 and TNF-α. GO and KEGG analysis reveals that berberine mainly plays a vital role by the signaling pathways of influenza, inflammation and immune response. Conclusion Berberine acts on TNF-α, STAT3, IL-6, CCL2 and other targets to inhibit inflammation and the activation of fibrocytes to achieve the purpose of treating COVID-19 pneumonia pulmonary fibrosis.

Identifies microtubule-binding protein CSPP1 as a novel cancer biomarker associated with ferroptosis and tumor microenvironment.

Centrosome and spindle pole-associated protein (CSPP1) is a centrosome and microtubule-binding protein that plays a role in cell cycle-dependent cytoskeleton organization and cilia formation. Previous studies have suggested that CSPP1 plays a role in tumorigenesis; however, no pan-cancer analysis has been performed. This study systematically investigates the expression of CSPP1 and its potential clinical outcomes associated with diagnosis, prognosis, and therapy. CSPP1 is widely present in tissues and cells and its aberrant expression serves as a diagnostic biomarker for cancer. CSPP1 dysregulation is driven by multi-dimensional mechanisms involving genetic alterations, DNA methylation, and miRNAs. Phosphorylation of CSPP1 at specific sites may play a role in tumorigenesis. In addition, CSPP1 correlates with clinical features and outcomes in multiple cancers. Take brain low-grade gliomas (LGG) with a poor prognosis as an example, functional enrichment analysis implies that CSPP1 may play a role in ferroptosis and tumor microenvironment (TME), including regulating epithelial-mesenchymal transition, stromal response, and immune response. Further analysis confirms that CSPP1 dysregulates ferroptosis in LGG and other cancers, making it possible for ferroptosis-based drugs to be used in the treatment of these cancers. Importantly, CSPP1-associated tumors are infiltrated in different TMEs, rendering immune checkpoint blockade therapy beneficial for these cancer patients. Our study is the first to demonstrate that CSPP1 is a potential diagnostic and prognostic biomarker associated with ferroptosis and TME, providing a new target for drug therapy and immunotherapy in specific cancers.

Interpopulation differences of retroduplication variations (RDVs) in rice retrogenes and their phenotypic correlations.

Retroduplication variation (RDV), a type of retrocopy polymorphism, is considered to have essential biological significance, but its effect on gene function and species phenotype is still poorly understood. To this end, we analyzed the retrocopies and RDVs in 3,010 rice genomes. We calculated the RDV frequencies in the genome of each rice population; detected the mutated, ancestral and expressed retrogenes in rice genomes; and analyzed their RDV influence on rice phenotypic traits. Collectively, 73 RDVs were identified, and 14 RDVs in ancestral retrogenes can significantly affect rice phenotypes. Our research reveals that RDV plays an important role in rice migration, domestication and evolution. We think that RDV is a good molecular breeding marker candidate. To our knowledge, this is the first study on the relationship between retrogene function, expression, RDV and species phenotype.

Identification of novel microRNAs and their targets in Chlorophytum borivilianum by small RNA and degradome sequencing.

Plant specific miRNAs (Novel miRNAs) are well known to perform distinctive functions in biological processes. Identification of new miRNAs is necessary to understand their gene regulation. Degradome provides an opportunity to explore the miRNA functions by comparing the miRNA population and their degraded products. In the present study, Small RNA sequencing data was used to identify novel miRNAs. Further, degradome sequencing was carried out to identify miRNAs targets in the plant, Chlorophytum borivilianum. The present study supplemented 40 more novel miRNAs correlating degradome data with smallRNAome. Novel miRNAs, complementary to mRNA partial sequences obtained from degradome sequencing were actually targeting the later. A big pool of miRNA was established by using Oryza sativa, Arabidopsis thaliana, Populus trichocarpa, Ricinus communis, and Vitis vinifera genomic data. Targets were identified for novel miRNAs and total 109 targets were predicted. BLAST2GO analysis elaborate about localization of novel miRNAs' targets and their corresponding KEGG (Kyoto Encyclopedia for Genes and Genomes) pathways. Identified targets were annotated and were found to be involved in significant biological processes like Nitrogen metabolism, Pyruvate metabolism, Citrate cycle (TCA cycle), photosynthesis, and Glycolysis/Gluconeogenesis. The present study provides an overall view of the miRNA regulation in multiple metabolic pathways that are involved in plant growth, pathogen resistance and secondary metabolism of C. borivilianum.

Differential expression profiles of long noncoding RNA and mRNA in colorectal cancer tissues from patients with lung metastasis.

Lungs are the most common extra­abdominal site of metastasis of colorectal cancer (CRC), in which long noncoding RNA (lncRNA) may serve a role. In the present study, a high­throughput microarray assay was performed to detect lncRNA expression and identify novel targets for further study of lung metastasis in CRC. In the CRC tissues from patients with lung metastasis, 7,632 lncRNA (3,574 upregulated and 4,058 downregulated) and 6,185 mRNA (3,394 upregulated and 2,791 downregulated) were detected to be differentially expressed with a fold change ≥2 and P<0.05 compared with the CRC tissues without metastasis. A total of six differentially regulated lncRNA were confirmed by reverse transcription­quantitative polymerase chain reaction in 20 pairs of CRC samples. Furthermore, gene ontology and pathway analysis were conducted to predict the possible roles of the identified mRNA. The upregulated mRNA were associated with cell division (biological processes), protein kinase B binding (molecular functions) and cellular components. The downregulated mRNA were associated with cell adhesion, platelet­derived growth factor binding and membrane components. Pathway analysis determined that the upregulated mRNA were associated with the Wnt signaling pathway in the CRC tissues from patients with lung metastasis, while the downregulated mRNA were associated with the phosphoinositide 3­kinase/Akt signaling pathway. The results of the present study suggested that differentially expressed lncRNA may be associated with lung metastasis and may provide insights into the biology and prevention of lung metastasis.