• Title/Summary/Keyword: functional enrichment

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FCAnalyzer: A Functional Clustering Analysis Tool for Predicted Transcription Regulatory Elements and Gene Ontology Terms

  • Kim, Sang-Bae;Ryu, Gil-Mi;Kim, Young-Jin;Heo, Jee-Yeon;Park, Chan;Oh, Berm-Seok;Kim, Hyung-Lae;Kimm, Ku-Chan;Kim, Kyu-Won;Kim, Young-Youl
    • Genomics & Informatics
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    • v.5 no.1
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    • pp.10-18
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    • 2007
  • Numerous studies have reported that genes with similar expression patterns are co-regulated. From gene expression data, we have assumed that genes having similar expression pattern would share similar transcription factor binding sites (TFBSs). These function as the binding regions for transcription factors (TFs) and thereby regulate gene expression. In this context, various analysis tools have been developed. However, they have shortcomings in the combined analysis of expression patterns and significant TFBSs and in the functional analysis of target genes of significantly overrepresented putative regulators. In this study, we present a web-based A Functional Clustering Analysis Tool for Predicted Transcription Regulatory Elements and Gene Ontology Terms (FCAnalyzer). This system integrates microarray clustering data with similar expression patterns, and TFBS data in each cluster. FCAnalyzer is designed to perform two independent clustering procedures. The first process clusters gene expression profiles using the K-means clustering method, and the second process clusters predicted TFBSs in the upstream region of previously clustered genes using the hierarchical biclustering method for simultaneous grouping of genes and samples. This system offers retrieved information for predicted TFBSs in each cluster using $Match^{TM}$ in the TRANSFAC database. We used gene ontology term analysis for functional annotation of genes in the same cluster. We also provide the user with a combinatorial TFBS analysis of TFBS pairs. The enrichment of TFBS analysis and GO term analysis is statistically by the calculation of P values based on Fisher’s exact test, hypergeometric distribution and Bonferroni correction. FCAnalyzer is a web-based, user-friendly functional clustering analysis system that facilitates the transcriptional regulatory analysis of co-expressed genes. This system presents the analyses of clustered genes, significant TFBSs, significantly enriched TFBS combinations, their target genes and TFBS-TF pairs.

Comparative Genomics Reveals the Core and Accessory Genomes of Streptomyces Species

  • Kim, Ji-Nu;Kim, Yeonbum;Jeong, Yujin;Roe, Jung-Hye;Kim, Byung-Gee;Cho, Byung-Kwan
    • Journal of Microbiology and Biotechnology
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    • v.25 no.10
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    • pp.1599-1605
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    • 2015
  • The development of rapid and efficient genome sequencing methods has enabled us to study the evolutionary background of bacterial genetic information. Here, we present comparative genomic analysis of 17 Streptomyces species, for which the genome has been completely sequenced, using the pan-genome approach. The analysis revealed that 34,592 ortholog clusters constituted the pan-genome of these Streptomyces species, including 2,018 in the core genome, 11,743 in the dispensable genome, and 20,831 in the unique genome. The core genome was converged to a smaller number of genes than reported previously, with 3,096 gene families. Functional enrichment analysis showed that genes involved in transcription were most abundant in the Streptomyces pan-genome. Finally, we investigated core genes for the sigma factors, mycothiol biosynthesis pathway, and secondary metabolism pathways; our data showed that many genes involved in stress response and morphological differentiation were commonly expressed in Streptomyces species. Elucidation of the core genome offers a basis for understanding the functional evolution of Streptomyces species and provides insights into target selection for the construction of industrial strains.

Transcriptome analysis of Panax ginseng response to high light stress

  • Jung, Je Hyeong;Kim, Ho-Youn;Kim, Hyoung Seok;Jung, Sang Hoon
    • Journal of Ginseng Research
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    • v.44 no.2
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    • pp.312-320
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    • 2020
  • Background: Ginseng (Panax ginseng Meyer) is an essential source of pharmaceuticals and functional foods. Ginseng productivity has been compromised by high light (HL) stress, which is one of the major abiotic stresses during the ginseng cultivation period. The genetic improvement for HL tolerance in ginseng could be facilitated by analyzing its genetic and molecular characteristics associated with HL stress. Methods: Genome-wide analysis of gene expression was performed under HL and recovery conditions in 1-year-old Korean ginseng (P. ginseng cv. Chunpoong) using the Illumina HiSeq platform. After de novo assembly of transcripts, we performed expression profiling and identified differentially expressed genes (DEGs). Furthermore, putative functions of identified DEGs were explored using Gene Ontology terms and Kyoto Encyclopedia of Genes and Genome pathway enrichment analysis. Results: A total of 438 highly expressed DEGs in response to HL stress were identified and selected from 29,184 representative transcripts. Among the DEGs, 326 and 114 transcripts were upregulated and downregulated, respectively. Based on the functional analysis, most upregulated and a significant number of downregulated transcripts were related to stress responses and cellular metabolic processes, respectively. Conclusion: Transcriptome profiling could be a strategy to comprehensively elucidate the genetic and molecular mechanisms of HL tolerance and susceptibility. This study would provide a foundation for developing breeding and metabolic engineering strategies to improve the environmental stress tolerance of ginseng.

Prebiotics enhance the biotransformation and bioavailability of ginsenosides in rats by modulating gut microbiota

  • Zhang, Xiaoyan;Chen, Sha;Duan, Feipeng;Liu, An;Li, Shaojing;Zhong, Wen;Sheng, Wei;Chen, Jun;Xu, Jiang;Xiao, Shuiming
    • Journal of Ginseng Research
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    • v.45 no.2
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    • pp.334-343
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    • 2021
  • Background: Gut microbiota mainly function in the biotransformation of primary ginsenosides into bioactive metabolites. Herein, we investigated the effects of three prebiotic fibers by targeting gut microbiota on the metabolism of ginsenoside Rb1 in vivo. Methods: Sprague Dawley rats were administered with ginsenoside Rb1 after a two-week prebiotic intervention of fructooligosaccharide, galactooligosaccharide, and fibersol-2, respectively. Pharmacokinetic analysis of ginsenoside Rb1 and its metabolites was performed, whilst the microbial composition and metabolic function of gut microbiota were examined by 16S rRNA gene amplicon and metagenomic shotgun sequencing. Results: The results showed that peak plasma concentration and area under concentration time curve of ginsenoside Rb1 and its intermediate metabolites, ginsenoside Rd, F2, and compound K (CK), in the prebiotic intervention groups were increased at various degrees compared with those in the control group. Gut microbiota dramatically responded to the prebiotic treatment at both taxonomical and functional levels. The abundance of Prevotella, which possesses potential function to hydrolyze ginsenoside Rb1 into CK, was significantly elevated in the three prebiotic groups (P < 0.05). The gut metagenomic analysis also revealed the functional gene enrichment for terpenoid/polyketide metabolism, glycolysis, gluconeogenesis, propanoate metabolism, etc. Conclusion: These findings imply that prebiotics may selectively promote the proliferation of certain bacterial stains with glycoside hydrolysis capacity, thereby, subsequently improving the biotransformation and bioavailability of primary ginsenosides in vivo.

Combined transcriptome and proteome analyses reveal differences in the longissimus dorsi muscle between Kazakh cattle and Xinjiang brown cattle

  • Yan, XiangMin;Wang, Jia;Li, Hongbo;Gao, Liang;Geng, Juan;Ma, Zhen;Liu, Jianming;Zhang, Jinshan;Xie, Penggui;Chen, Lei
    • Animal Bioscience
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    • v.34 no.9
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    • pp.1439-1450
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    • 2021
  • Objective: With the rapid development of proteomics sequencing and RNA sequencing technology, multi-omics analysis has become a current research hotspot. Our previous study indicated that Xinjiang brown cattle have better meat quality than Kazakh cattle. In this study, Xinjiang brown cattle and Kazakh cattle were used as the research objects. Methods: Proteome sequencing and RNA sequencing technology were used to analyze the proteome and transcriptome of the longissimus dorsi muscle of the two breeds of adult steers (n = 3). Results: In this project, 22,677 transcripts and 1,874 proteins were identified through quantitative analysis of the transcriptome and proteome. By comparing the identified transcriptome and proteome, we found that 1,737 genes were identified at both the transcriptome and proteome levels. The results of the study revealed 12 differentially expressed genes and proteins: troponin I1, crystallin alpha B, cysteine, and glycine rich protein 3, phosphotriesterase-related, myosin-binding protein H, glutathione s-transferase mu 3, myosin light chain 3, nidogen 2, dihydropyrimidinase like 2, glutamate-oxaloacetic transaminase 1, receptor accessory protein 5, and aspartoacylase. We performed functional enrichment of these differentially expressed genes and proteins. The Kyoto encyclopedia of genes and genomes results showed that these differentially expressed genes and proteins are enriched in the fatty acid degradation and histidine metabolism signaling pathways. We performed parallel reaction monitoring (PRM) verification of the differentially expressed proteins, and the PRM results were consistent with the sequencing results. Conclusion: Our study provided and identified the differentially expressed genes and proteins. In addition, identifying functional genes and proteins with important breeding value will provide genetic resources and technical support for the breeding and industrialization of new genetically modified beef cattle breeds.

A genome-wide approach to the systematic and comprehensive analysis of LIM gene family in sorghum (Sorghum bicolor L.)

  • Md. Abdur Rauf Sarkar;Salim Sarkar;Md Shohel Ul Islam;Fatema Tuz Zohra;Shaikh Mizanur Rahman
    • Genomics & Informatics
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    • v.21 no.3
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    • pp.36.1-36.19
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    • 2023
  • The LIM domain-containing proteins are dominantly found in plants and play a significant role in various biological processes such as gene transcription as well as actin cytoskeletal organization. Nevertheless, genome-wide identification as well as functional analysis of the LIM gene family have not yet been reported in the economically important plant sorghum (Sorghum bicolor L.). Therefore, we conducted an in silico identification and characterization of LIM genes in S. bicolor genome using integrated bioinformatics approaches. Based on phylogenetic tree analysis and conserved domain, we identified five LIM genes in S. bicolor (SbLIM) genome corresponding to Arabidopsis LIM (AtLIM) genes. The conserved domain, motif as well as gene structure analyses of the SbLIM gene family showed the similarity within the SbLIM and AtLIM members. The gene ontology (GO) enrichment study revealed that the candidate LIM genes are directly involved in cytoskeletal organization and various other important biological as well as molecular pathways. Some important families of regulating transcription factors such as ERF, MYB, WRKY, NAC, bZIP, C2H2, Dof, and G2-like were detected by analyzing their interaction network with identified SbLIM genes. The cis-acting regulatory elements related to predicted SbLIM genes were identified as responsive to light, hormones, stress, and other functions. The present study will provide valuable useful information about LIM genes in sorghum which would pave the way for the future study of functional pathways of candidate SbLIM genes as well as their regulatory factors in wet-lab experiments.

Strategy for enhancing Production of recombinant Protein in tobacco's suspension culture

  • Lee, Dong-Geun;Lee, Jae-Hwa
    • Proceedings of the Korean Society of Life Science Conference
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    • 2002.12a
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    • pp.48-60
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    • 2002
  • Granulocyte-macrophage colony-stimulating factor (GM-CSF) is a cytokine that stimulates the production of granulocytes, macrophages, and white blood cells. The effects of osmotic pressure on secretion of human GM-CSF into the culture medium were investigated in suspension cultures of transgenic tobacco cells. An increase in osmotic pressure caused by the addition of mannitol decreased the cell size index, with the effect being more pronounced when cells were measured wet rather than dry. Increased osmotic pressure enhanced the secretion of hGM-CSF. At 90 g/L mannitol, the maximum concentration tested, hGM-CSF was present in the culture medium at 980 ug/L. As the concentration of mannitol increased, the total amount of protein secreted also increased, but was disproportionately enriched in GM-CSF NaCl, another osmoticum, had very similar effects on cell growth and hGM-CSF production, but did not cause enrichment for hGM-CSF Additionally, protein-stabilizing polymer was added to culture broth to enhance stability of secreted recombinant protein. Finally, above two method were applied together to maximize the productivity.

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Exploration of Molecular Mechanisms of Diffuse Large B-cell Lymphoma Development Using a Microarray

  • Zhang, Zong-Xin;Shen, Cui-Fen;Zou, Wei-Hua;Shou, Li-Hong;Zhang, Hui-Ying;Jin, Wen-Jun
    • Asian Pacific Journal of Cancer Prevention
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    • v.14 no.3
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    • pp.1731-1735
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    • 2013
  • Objective: We aimed to identify key genes, pathways and function modules in the development of diffuse large B-cell lymphoma (DLBCL) with microarray data and interaction network analysis. Methods: Microarray data sets for 7 DLBCL samples and 7 normal controls was downloaded from the Gene Expression Omnibus (GEO) database and differentially expressed genes (DEGs) were identified with Student's t-test. KEGG functional enrichment analysis was performed to uncover their biological functions. Three global networks were established for immune system, signaling molecules and interactions and cancer genes. The DEGs were compared with the networks to observe their distributions and determine important key genes, pathways and modules. Results: A total of 945 DEGs were obtained, 272 up-regulated and 673 down-regulated. KEGG analysis revealed that two groups of pathways were significantly enriched: immune function and signaling molecules and interactions. Following interaction network analysis further confirmed the association of DEGs in immune system, signaling molecules and interactions and cancer genes. Conclusions: Our study could systemically characterize gene expression changes in DLBCL with microarray technology. A range of key genes, pathways and function modules were revealed. Utility in diagnosis and treatment may be expected with further focused research.

Analysis of Different Activation Statuses of Human Mammary Epithelial Cells from Young and Old Groups

  • Feng, Chen-Chen;Chen, Li-Na;Chen, Mei-Jun;Li, Wan;Jia, Xu;Zhou, Yan-Yan;He, Wei-Ming
    • Asian Pacific Journal of Cancer Prevention
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    • v.15 no.8
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    • pp.3763-3766
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    • 2014
  • Human mammary epithelial cells have different proliferative statuses and demonstrate a close relationship with age and cell proliferation. Research on this topic could help understand the occurrence, progression and prognosis of breast cancer. In this article, using significance analysis of a microarray algorithm, we analyzed gene expression profiles of human mammary epithelial cells of different proliferative statuses and different age groups. The results showed there were significant differences in gene expression in the same proliferation status between elderly and young groups. Three common differentially expressed genes were found to dynamically change with the proliferation status and to be closely related to tumorigenesis. We also found elderly group had less status-related differential genes from actively proliferating status to intermediate status and more statusrelated differential genes from intermediate status than the young group. Finally, functional enrichment analyses allowed evaluation of the detailed roles of these differentially-expressed genes in tumor progression.

Analysis of Gene Expression in Mouse Spinal Cord-derived Neural Precursor Cells During Neuronal Differentiation

  • Ahn, Joon-Ik;Kim, So-Young;Ko, Moon-Jeong;Chung, Hye-Joo;Jeong, Ho-Sang
    • Genomics & Informatics
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    • v.7 no.2
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    • pp.85-96
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    • 2009
  • The differentiation of neural precursor cells (NPCs) into neurons and astrocytes is a process that is tightly controlled by complicated and ill-defined gene networks. To extend our knowledge to gene networks, we performed a temporal analysis of gene expression during the differentiation (2, 4, and 8 days) of spinal cord-derived NPCs using oligonucleotide microarray technology. Out of 32,996 genes analyzed, 1878 exhibited significant changes in expression level (fold change>2, p<0.05) at least once throughout the differentiation process. These 1878 genes were classified into 12 groups by k-means clustering, based on their expression patterns. K-means clustering analysis revealed that the genes involved in astrogenesis were categorized into the clusters containing constantly upregulated genes, whereas the genes involved in neurogenesis were grouped to the cluster showing a sudden decrease in gene expression on Day 8. Functional analysis of the differentially expressed genes indicated the enrichment of genes for Pax6- NeuroD signaling.TGFb-SMAD and BMP-SMAD.which suggest the implication of these genes in the differentiation of NPCs and, in particular, key roles for Nova1 and TGFBR1 in the neurogenesis/astrogenesis of mouse spinal cord.