Objective: Hemicastration is a unilateral orchiectomy to remove an injured testis, which can induce hormonal changes and compensatory hypertrophy of the remaining testis, and may influence spermatogenesis. However, the underlying molecular mechanisms are poorly understood. Here, we investigated the impact of hemicastration on remaining testicular function. Methods: Prepubertal mice (age 24 days) were hemicastrated, and their growth was monitored until they reached physical maturity (age 72 days). Subsequently, we determined testis DNA methylation patterns using reduced representation bisulfite sequencing of normal and hemicastrated mice. Moreover, we profiled the testicular gene expression patterns by RNA sequencing (RNA-seq) to examine whether methylation changes affected gene expression in hemicastrated mice. Results: Hemicastration did not significantly affect growth or testosterone (p>0.05) compared with control. The genome-wide DNA methylation pattern of remaining testis suggested that substantial genes harbored differentially methylated regions (1,139) in gene bodies, which were enriched in process of protein binding and cell adhesion. Moreover, RNA-seq results indicated that 46 differentially expressed genes (DEGs) involved in meiotic cell cycle, synaptonemal complex assembly and spermatogenesis were upregulated in the hemicastration group, while 197 DEGs were downregulated, which were related to arachidonic acid metabolism. Integrative analysis revealed that proteasome 26S subunit ATPase 3 interacting protein gene, which encodes a protein crucial for homologous recombination in spermatocytes, exhibited promoter hypomethylation and higher expression level in hemicastrated mice. Conclusion: Global profiling of DNA methylation and gene expression demonstrated that hemicastration-induced compensatory response maintained normal growth and testicular morphological structure in mice.
Seed germination is the important stage to express many genes for regulation of energy metabolism, starch degradation and cell division from seed dormancy state. For the functional analysis of seed germination mechanisms, we were analyzed the rice cDNA clones (Oryzasativa cultivar Ilpum) obtained from seed imbibition during 48 hours. Total number of 18,101 Expressed Sequence Tags (ESTs) were clustered using SeqMan program. Among them, 8,836 clones were identified as unique clones. We identified the chitinase gene specifically expressed in seed germination and amylase gene involved to starch degradation from the full length cDNA analysis, and several genes were registered to NCBI GeneBank. To analyzed the commonly expressed genes between inmature seed and germinated seed, 25,66 inmature ESTs and 18,101 germinated ESTs were clustered using SeqMan program and identified 2,514 clones as commonly expressed unigene. Among them, alpha-glubulin and alcohol dehydrogenase I were supposed to LEA genes only expressed in the immature and germinated seed stages. For the clustering of orthologous group genes, we further analyzed the 8,836 EST clones from germinating seeds using NCBI clusters of orthologous groups database. Among the clones, 5,076 clones were categorized into information storage and processing, cellular processes and signaling, metabolism and poorly characterized genes, proportioning 783 (14.29%), 1,484 (27%), 1,363 (24.8%) and 1,869 (34%) clones to the previous four categories, respectively.
Sa, Kyu Jin;Choi, Ik?Young;Park, Kyong?Cheul;Lee, Ju Kyong
Genes and Genomics
/
제40권12호
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pp.1319-1329
/
2018
SSRs were successfully isolated from the Perilla crop in our current study, and used to analyze Perilla accessions from East Asia. Analyses of the clear genetic diversity and relationship for Perilla crop still remain insufficient. In this study, 40 new simple sequence repeat (SSR) primer sets were developed from RNA sequences using transcriptome analysis. These new SSR markers were applied to analyze the diversity, relationships, and population structure among 35 accessions of the two cultivated types of Perilla crop and their weedy types. A total of 220 alleles were identified at all loci, with an average of 5.5 alleles per locus and a range between 2 and 10 alleles per locus. The MAF (major allele frequency) per locus varied from 0.229 to 0.943, with an average of 0.466. The average polymorphic information content (PIC) value was 0.603, ranging from 0.102 to 0.837. The genetic diversity (GD) ranged from 0.108 to 0.854, with an average of 0.654. Based on population structure analysis, all accessions were divided into three groups: Group I, Group II and the admixed group. This study demonstrated the utility of new SSR analysis for the study of genetic diversity and population structure among 35 Perilla accessions. The GD of each locus for accessions of cultivated var. frutescens, weedy var. frutescens, cultivated var. crispa, and weedy var. crispa were 0.415, 0.606, 0.308, and 0.480, respectively. Both weedy accessions exhibited higher GD and PIC values than their cultivated types in East Asia. The new SSR primers of Perilla species reported in this study may provide potential genetic markers for population genetics to enhance our understanding of the genetic diversity, genetic relationship and population structure of the cultivated and weedy types of P. frutescens in East Asia. In addition, new Perilla SSR primers developed from RNA-seq can be used in the future for cultivar identification, conservation of Perilla germplasm resources, genome mapping and tagging of important genes/QTLs for Perilla breeding programs.
Jo, Hye-Yeong;Kim, Sang Cheol;Ahn, Do-hwan;Lee, Siyoung;Chang, Se-Hyun;Jung, So-Young;Kim, Young-Jin;Kim, Eugene;Kim, Jung-Eun;Kim, Yeon-Sook;Park, Woong-Yang;Cho, Nam-Hyuk;Park, Donghyun;Lee, Ju-Hee;Park, Hyun-Young
BMB Reports
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제55권9호
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pp.465-471
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2022
Understanding and monitoring virus-mediated infections has gained importance since the global outbreak of the coronavirus disease 2019 (COVID-19) pandemic. Studies of high-throughput omics-based immune profiling of COVID-19 patients can help manage the current pandemic and future virus-mediated pandemics. Although COVID-19 is being studied since past 2 years, detailed mechanisms of the initial induction of dynamic immune responses or the molecular mechanisms that characterize disease progression remains unclear. This study involved comprehensively collected biospecimens and longitudinal multi-omics data of 300 COVID-19 patients and 120 healthy controls, including whole genome sequencing (WGS), single-cell RNA sequencing combined with T cell receptor (TCR) and B cell receptor (BCR) sequencing (scRNA(+scTCR/BCR)-seq), bulk BCR and TCR sequencing (bulk TCR/BCR-seq), and cytokine profiling. Clinical data were also collected from hospitalized COVID-19 patients, and HLA typing, laboratory characteristics, and COVID-19 viral genome sequencing were performed during the initial diagnosis. The entire set of biospecimens and multi-omics data generated in this project can be accessed by researchers from the National Biobank of Korea with prior approval. This distribution of large-scale multi-omics data of COVID-19 patients can facilitate the understanding of biological crosstalk involved in COVID-19 infection and contribute to the development of potential methodologies for its diagnosis and treatment.
Anh Duc Truong;Ha Thi Thanh Tran;Nhu Thi Chu;Huyen Thi Nguyen;Thi Hao Vu;Yeojin Hong;Ki-Duk Song;Hoang Vu Dang;Yeong Ho Hong
Animal Bioscience
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제36권4호
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pp.570-583
/
2023
Objective: Fibroblast growth factors (FGFs) play critical roles in embryo development, and immune responses to infectious diseases. In this study, to investigate the roles of FGFs, we performed genome-wide identification, expression, and functional analyses of FGF family members in chickens. Methods: Chicken FGFs genes were identified and analyzed by using bioinformatics approach. Expression profiles and Hierarchical cluster analysis of the FGFs genes in different chicken tissues were obtained from the genome-wide RNA-seq. Results: A total of 20 FGF genes were identified in the chicken genome, which were classified into seven distinct groups (A-F) in the phylogenetic tree. Gene structure analysis revealed that members of the same clade had the same or similar exon-intron structure. Chromosome mapping suggested that FGF genes were widely dispersed across the chicken genome and were located on chromosomes 1, 4-6, 9-10, 13, 15, 28, and Z. In addition, the interactions among FGF proteins and between FGFs and mitogen-activated protein kinase (MAPK) proteins are limited, indicating that the remaining functions of FGF proteins should be further investigated in chickens. Kyoto encyclopedia of genes and genomes pathway analysis showed that FGF gene interacts with MAPK genes and are involved in stimulating signaling pathway and regulating immune responses. Furthermore, this study identified 15 differentially expressed genes (DEG) in 21 different growth stages during early chicken embryo development. RNA-sequencing data identified the DEG of FGFs on 1- and 3-days post infection in two indigenous Ri chicken lines infected with the highly pathogenic avian influenza virus H5N1 (HPAIV). Finally, all the genes examined through quantitative real-time polymerase chain reaction and RNA-Seq analyses showed similar responses to HPAIV infection in indigenous Ri chicken lines (R2 = 0.92-0.95, p<0.01). Conclusion: This study provides significant insights into the potential functions of FGFs in chickens, including the regulation of MAPK signaling pathways and the immune response of chickens to HPAIV infections.
Lu Xu;Zhongliang Wang;Shihao Liu;Zhiheng Wei;Jianfeng Yu;Jun Li;Jie Li;Wen Yao;Zhiliang Gu
Animal Bioscience
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제37권3호
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pp.437-450
/
2024
Objective: Vanin-1 (VNN1) is a pantetheinase that catalyses the hydrolysis of pantetheine to produce pantothenic acid and cysteamine. Our previous studies have shown that the VNN1 is specifically expressed in chicken liver which negatively regulated by microRNA-122. However, the functions of the VNN1 in lipid metabolism in chicken liver haven't been elucidated. Methods: First, we detected the VNN1 mRNA expression in 4-week chickens which were fasted 24 hours. Next, knocked out VNN1 via CRISPR/Cas9 system in the chicken Leghorn Male Hepatoma cell line. Detected the lipid deposition via oil red staining and analysis the content of triglycerides (TG), low-density lipoprotein-C (LDL-C), and high-density lipoprotein-C (HDL-C) after VNN1 knockout in Leghorn Male Hepatoma cell line. Then we captured various differentially expressed genes (DEGs) between VNN1-modified LMH cells and original LMH cells by RNA-seq. Results: Firstly, fasting-induced expression of VNN1. Meanwhile, we successfully used the CRISPR/Cas9 system to achieve targeted mutations of the VNN1 in the chicken LMH cell line. Moreover, the expression level of VNN1 mRNA in LMH-KO-VNN1 cells decreased compared with that in the wild-type LMH cells (p<0.0001). Compared with control, lipid deposition was decreased after knockout VNN1 via oil red staining, meanwhile, the contents of TG and LDL-C were significantly reduced, and the content of HDL-C was increased in LMH-KO-VNN1 cells. Transcriptome sequencing showed that there were 1,335 DEGs between LMH-KO-VNN1 cells and original LMH cells. Of these DEGs, 431 were upregulated, and 904 were downregulated. Gene ontology analyses of all DEGs showed that the lipid metabolism-related pathways, such as fatty acid biosynthesis and long-chain fatty acid biosynthesis, were enriched. KEGG pathway analyses showed that "lipid metabolism pathway", "energy metabolism", and "carbohydrate metabolism" were enriched. A total of 76 DEGs were involved in these pathways, of which 29 genes were upregulated (such as cytochrome P450 family 7 subfamily A member 1, ELOVL fatty acid elongase 2, and apolipoprotein A4) and 47 genes were downregulated (such as phosphoenolpyruvate carboxykinase 1) by VNN1 knockout in the LMH cells. Conclusion: These results suggest that VNN1 plays an important role in coordinating lipid metabolism in the chicken liver.
The coronavirus disease 2019 (COVID-19) pandemic (severe acute respiratory syndrome coronavirus 2) is a global infectious disease with rapid spread. Some patients have severe symptoms and clinical signs caused by an excessive inflammatory response, which increases the risk of mortality. In this study, we reanalyzed scRNA-seq data of cells from bronchoalveolar lavage fluids of patients with COVID-19 with mild and severe symptoms, focusing on Ab-producing cells. In patients with severe disease, B cells seemed to be more activated and expressed more immunoglobulin genes compared with cells from patients with mild disease, and macrophages expressed higher levels of the TNF superfamily member B-cell activating factor but not of APRIL (a proliferation-inducing ligand). In addition, macrophages from patients with severe disease had increased pro-inflammatory features and pathways associated with Fc receptor-mediated signaling, compared with patients with mild disease. CCR2-positive plasma cells accumulated in patients with severe disease, probably because of increased CCL2 expression on macrophages from patients with severe disease. Together, these results support the hypothesis that different characteristics of B cells might be associated with the severity of COVID-19 infection.
Purpose: Culture-based methods for microbiological diagnosis and antibiotic susceptibility tests have limitations in the management of orofacial infections. We aimed to profile pus microbiota and identify antibiotic resistance genes (ARGs) using a culture-independent approach. Materials and Methods: Genomic DNA samples extracted from the pus specimens of two patients with orofacial abscesses were subjected to shotgun sequencing on the NovaSeq system. Taxonomic profiling and prediction of ARGs were performed directly from the metagenomic raw reads. Result: Taxonomic profiling revealed obligate anaerobic polymicrobial communities associated with infections of odontogenic origins: the microbial community of Patient 1 consisted of one predominant species (Prevotella oris 74.6%) with 27 minor species, while the sample from Patient 2 contained 3 abundant species (Porphyromonas endodontalis 33.0%; P. oris 31.6%; and Prevotella koreensis 13.4%) with five minor species. A total of 150 and 136 putative ARGs were predicted in the metagenome of each pus sample. The coverage of most predicted ARGs was less than 10%, and only the CfxA2 gene identified in Patient 1 was covered 100%. ARG analysis of the seven assembled genome/metagenome datasets of P. oris revealed that strain C735 carried the CfxA2 gene. Conclusion: A metagenomics-based approach is useful to profile predominantly anaerobic polymicrobial communities but needs further verification for reliable ARG detection.
Breast cancer (BRC) is the most invasive cancer in women. Although the survival rate of BRC is gradually increasing due to improved screening systems, development of novel therapeutic targets for inhibition of BRC proliferation, metastasis and recurrence have been constantly needed. Thus, in this study, we identified overexpression of SETDB1 (SET Domain Bifurcated 1), a histone methyltransferase, in RNA-seq data of BRC derived from TCGA portal. In Gene Ontology (GO) analysis, cell migration-related GO terms were enriched, and we confirmed down-regulation of cell migration/invasion and alteration of EMT /MET markers after knockdown of SETDB1. Moreover, gene network analysis showed that SMAD7 expression is regulated by SETDB1 levels, indicating that up-regulation of SMAD7 by SETDB1 knockdown inhibited BRC metastasis. Therefore, development of SETDB1 inhibitors and functional studies may help develop more effective clinical guidelines for BRC treatment.
Multi-omics data is difficult to interpret due to the heterogeneity of information by the volume of data, the complexity of characteristics of each data, and the diversity of omics platforms. There is not yet a system for interpreting to visualize research data on environmental diseases concerning environmental harmful substances. We provide MEE, a web-based visualization tool, to comprehensively explore the complexity of data due to the interconnected characteristics of high-dimensional data sets according to exposure to various environmental harmful substances. MEE visualizes omics data of correlation between omics data, subjects and samples by keyword searches of meta data, multi-omics data, and harmful substances. MEE has been demonstrated the versatility by two examples. We confirmed the correlation between smoking and asthma with RNA-seq and Methylation-Chip data, it was visualized that genes (P HACTR3, PXDN, QZMB, SOCS3 etc.) significantly related to autoimmune or inflammatory diseases. To visualize the correlation between atopic dermatitis and heavy metals, we selected 32 genes related immune response by integrated analysis of multi-omics data. However, it did not show a significant correlation between mercury in blood and atopic dermatitis. In the future, should continuously collect an appropriate level of multi-omics data in MEE system, will obtain data to analyze environmental substances and diseases.
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