• Asian-Australasian Journal of Animal Sciences
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• v.32 no.12
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• pp.1816-1825
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• 2019

Objective: We tried to analyze allele-specific expression in the pig neocortex using bioinformatic analysis of high-throughput sequencing results from the parental genomes and offspring transcriptomes from reciprocal crosses between Korean Native and Landrace pigs. Methods: We carried out sequencing of parental genomes and offspring transcriptomes using next generation sequencing. We subsequently carried out genome scale identification of single nucleotide polymorphisms (SNPs) in two different ways using either individual genome mapping or joint genome mapping of the same breed parents that were used for the reciprocal crosses. Using parent-specific SNPs, allele-specifically expressed genes were analyzed. Results: Because of the low genome coverage (${\sim}4{\times}$) of the sequencing results, most SNPs were non-informative for parental lineage determination of the expressed alleles in the offspring and were thus excluded from our analysis. Consequently, 436 SNPs covering 336 genes were applicable to measure the imbalanced expression of paternal alleles in the offspring. By calculating the read ratios of parental alleles in the offspring, we identified seven genes showing allele-biased expression (p<0.05) including three previously reported and four newly identified genes in this study. Conclusion: The newly identified allele-specifically expressing genes in the neocortex of pigs should contribute to improving our knowledge on genomic imprinting in pigs. To our knowledge, this is the first study of allelic imbalance using high throughput analysis of both parental genomes and offspring transcriptomes of the reciprocal cross in outbred animals. Our study also showed the effect of the number of informative animals on the genome level investigation of allele-specific expression using RNA-seq analysis in livestock species.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.10
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• pp.1483-1490
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• 2019

Objective: To explore the molecular mechanisms of fat metabolism and deposition in pigs, an experiment was conducted to identify hepatic mRNAs and miRNAs expression and determine the potential interaction of them in two phenotypically extreme pig breeds. Methods: mRNA and miRNA profiling of liver from 70-day Jinhua (JH) and Landrace (LD) pigs were performed using RNA sequencing. Blood samples were taken to detect results of serum biochemistry. Bioinformatics analysis were applied to construct differentially expressed miRNA-mRNA network. Results: Serum total triiodothyronine and total thyroxine were significantly lower in Jinhua pigs, but the content of serum total cholesterol (TCH) and low-density lipoprotein cholesterol were strikingly higher. A total of 467 differentially expressed genes (DEGs) and 35 differentially expressed miRNAs (DE miRNAs) were identified between JH and LD groups. Gene ontology analysis suggested that DEGs were involved in oxidation-reduction, lipid biosynthetic and lipid metabolism process. Interaction network of DEGs and DE miRNAs were constructed, according to target prediction results. Conclusion: We generated transcriptome and miRNAome profiles of liver from JH and LD pig breeds which represent distinguishing phenotypes of growth and metabolism. The potential miRNA-mRNA interaction networks may provide a comprehensive understanding in the mechanism of lipid metabolism. These results serve as a basis for further investigation on biological functions of miRNAs in the porcine liver.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.5
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• pp.696-703
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• 2020

Objective: Cattle were some of the first animals domesticated by humans for the production of milk, meat, etc. Long noncoding RNA (lncRNA) is defined as longer than 200 bp in nonprotein coding transcripts. lncRNA is known to function in regulating gene expression and is currently being studied in a variety of livestock including cattle. The purpose of this study is to analyze the characteristics of lncRNA according to sex in Hanwoo cattle. Methods: This study was conducted using the skeletal muscles of 9 Hanwoo cattle include bulls, steers and cows. RNA was extracted from skeletal muscle of Hanwoo. Sequencing was conducted using Illumina HiSeq2000 and mapped to the Bovine Taurus genome. The expression levels of lncRNAs were measured by DEGseq and quantitative trait loci (QTL) data base was used to identify QTLs associated with lncRNA. The python script was used to match the nearby genes Results: In this study, the expression patterns of transcripts of bulls, steers and cows were identified. And we identified significantly differentially expressed lncRNAs in bulls, steers and cows. In addition, characteristics of lncRNA which express differentially in muscles according to the sex of Hanwoo were identified. As a result, we found differentially expressed lncRNAs according to sex were related to shear force and body weight. Conclusion: This study was classified and characterized lncRNA which differentially expressed by sex in Hanwoo cattle. We believe that the characterization of lncRNA by sex of Hanwoo will be helpful for future studies of the physiological mechanisms of Hanwoo cattle.

• Korean Journal of Poultry Science
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• v.44 no.3
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• pp.199-209
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• 2017

Mitogen-activated protein kinase (MAPK) signaling pathways play a key role in innate immunity, inflammation, cell proliferation, cell differentiation, and cell death. The main objective of this study was to investigate the expression level of candidate MAPK pathway genes in the intestinal mucosal layer of two genetically disparate chicken lines (Marek's disease-resistant line 6.3 and Marek's disease-susceptible line 7.2) induced with necrotic enteritis (NE). Using high-throughput RNA sequencing, we investigated 178 MAPK signaling pathway related genes that were significantly and differentially expressed between the intestinal mucosal layers of the NE-afflicted and control chickens. In total, 15 MAPK pathway genes were further measured by quantitative real-time PCR(qRT-PCR) and the results were consistent with the RNA-sequencing data. All 178 identified genes were annotated through Gene Ontology and mapped onto the KEGG chicken MAPK signaling pathway. Several key genes of the MAPK pathway, ERK1/2, JNK1-3, p38 MAPK, MAP2K1-4, $NF-{\kappa}B1/2$, c-Fos, AP-1, Jun-D, and Jun, were differentially expressed in the two chicken lines. Therefore, we believe that RNA sequencing and qRT-PCR analysis provide resourceful information for future studies on MAPK signaling of genetically disparate chicken lines in response to pathogens.

• Journal of Internet Computing and Services
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• v.18 no.5
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• pp.47-53
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• 2017

In past few years, high-throughput sequencing, big-data generation, cloud computing, and computational biology are revolutionary. RNA sequencing is emerging as an attractive alternative to DNA microarrays. And the methods for constructing Gene Regulatory Network (GRN) from RNA-Seq are extremely lacking and urgently required. Because GRN has obtained substantial observation from genomics and bioinformatics, an elementary requirement of the GRN has been to maximize distinguishable genes. Despite of RNA sequencing techniques to generate a big amount of data, there are few computational methods to exploit the huge amount of the big data. Therefore, we have suggested a novel gene selection algorithm combining Support Vector Machines and Intensity-dependent normalization, which uses log differential expression ratio in RNAseq. It is an extended variation of support vector machine recursive feature elimination (SVM-RFE) algorithm. This algorithm accomplishes minimum relevancy with subsets of Big-Data, such as NCBI-GEO. The proposed algorithm was compared to the existing one which uses gene expression profiling DNA microarrays. It finds that the proposed algorithm have provided as convenient and quick method than previous because it uses all functions in R package and have more improvement with regard to the classification accuracy based on gene ontology and time consuming in terms of Big-Data. The comparison was performed based on the number of genes selected in RNAseq Big-Data.

• Molecules and Cells
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• v.45 no.5
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• pp.317-328
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• 2022

Trophoblasts, important functional cells in the placenta, play a critical role in maintaining placental function. The heterogeneity of trophoblasts has been reported, but little is known about the trophoblast subtypes and distinctive functions during preeclampsia (PE). In this study, we aimed to gain insight into the cell type-specific transcriptomic changes by performing unbiased single-cell RNA sequencing (scRNA-seq) of placental tissue samples, including those of patients diagnosed with PE and matched healthy controls. A total of 29,006 cells were identified in 11 cell types, including trophoblasts and immune cells, and the functions of the trophoblast subtypes in the PE group and the control group were also analyzed. As an important trophoblast subtype, extravillous trophoblasts (EVTs) were further divided into 4 subgroups, and their functions were preliminarily analyzed. We found that some biological processes related to pregnancy, hormone secretion and immunity changed in the PE group. We also identified and analyzed the regulatory network of transcription factors (TFs) identified in the EVTs, among which 3 modules were decreased in the PE group. Then, through in vitro cell experiments, we found that in one of the modules, CEBPB and GTF2B may be involved in EVT dysfunction in PE. In conclusion, our study showed the different transcriptional profiles and regulatory modules in trophoblasts between placentas in the control and PE groups at the single-cell level; these changes may be involved in the pathological process of PE, providing a new molecular theoretical basis for preeclamptic trophoblast dysfunction.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2019.10a
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• pp.73-73
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• 2019

Angelica gigas Nakai (Korean danggui), a member of the Umbelliferae family, is a Korean traditional medicinal plant whose roots have been used for treating gynecological diseases. Transcriptomics is the study of the transcriptome, which is the complete set of RNA transcripts that are produced by the genome, using high-throughput methods, such as microarray analysis. In this study, transcriptome analysis of A.gigas Nakai was carried out. Transcriptome sequencing and assembly was carried out by using Illumina Hiseq 2500, Velvet and Oases. A total of 109,591,555 clean reads of A. gigas Nakai was obtained after trimming adaptors. The obtained reads were assembled with an average length of 1,154 bp, a maximum length of 13,166 bp, a minimum length of 200 pb, and N50 of 1,635 bp. Functional annotation and classification was performed using NCBI NR, InterprotScan, KOG, KEGG and GO. Candidate genes for phenylpropanoid biosynthesis were obtanied from A.gigas transcriptome and the genes and its proteins were confirmed through the NCBI homology BLAST searches, revealing high identity with other othologous genes and proteins from various plants pecies. In RNA sequencing analysis using an Illumina Next-Seq2500 sequencer, we identified a total 94,930 transcripts and annotated 71,281 transcripts, which provide basic information for further research in A.gigas Nakai. Our transcriptome data reveal that several differentially expressed genes related to flower color in A.gigas Nakai. The results of this research provide comprehensive information on the A.gigas Nakai genome and enhance our understanding of the flower color related gene pathways in this plant.

• Korean Journal of Microbiology
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• v.55 no.3
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• pp.220-225
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• 2019

Studies based on microbial community analyses have increased in the recent decade since the development of next generation sequencing technology. Associations of gut microbiota with host's health are one of the major outcomes of microbial ecology filed. The major approach for microbial community analysis includes the sequencing of variable regions of 16S rRNA genes, which does not provide the information of bacterial activities. Here, we conducted RNA-based microbial community analysis and compared results obtained from DNA- and its cDNA-based microbial community analyses. Our results indicated that these two approaches differed in the ratio of Firmicutes and Bacteroidetes, known as an obesity indicator, as well as abundance of some key bacteria in gut metabolisms such as butyrate producers and probiotics strains. Therefore, cDNA-based microbial community may provide different insights regarding roles of gut microbiota compared to the previous studies where DNA-based microbial community analyses were performed.

• Asian-Australasian Journal of Animal Sciences
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• v.28 no.2
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• pp.158-165
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• 2015

Marbling is an important trait regarding the quality of beef. Analysis of beef cattle transcriptome and its expression profile data are essential to extend the genetic information resources and would support further studies on beef cattle. RNA sequencing was performed in beef cattle using the Illumina High-Seq2000 platform. Approximately 251.58 million clean reads were generated from a high marbling (H) group and low marbling (L) group. Approximately 80.12% of the 19,994 bovine genes (protein coding) were detected in all samples, and 749 genes exhibited differential expression between the H and L groups based on fold change (>1.5-fold, p<0.05). Multiple gene ontology terms and biological pathways were found significantly enriched among the differentially expressed genes. The transcriptome data will facilitate future functional studies on marbling formation in beef cattle and may be applied to improve breeding programs for cattle and closely related mammals.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2018.04a
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• pp.5-5
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• 2018

Ginseng (Panax ginseng C.A. Meyer), one of the most widely used medicinal plants in traditional oriental medicine, is used for the treatment of various diseases. It has been classified according to its cultivation environment, such as field cultivated ginseng (FCG) and mountain cultivated ginseng (MCG). However, little is known about differences in gene expression in ginseng roots between field cultivated and mountain cultivated ginseng. In order to investigate the whole transcriptome landscape of ginseng, we employed High-Throughput sequencing technologies using the Illumina HiSeqTM2500 system, and generated a large amount of sequenced transcriptome from ginseng roots. Approximately 77 million and 87 million high-quality reads were produced in the FCG and MCG roots transcriptome analyses, respectively, and we obtained 256,032 assembled unigenes with an average length of 1,171 bp by de novo assembly methods. Functional annotations of the unigenes were performed using sequence similarity comparisons against the following databases: the non-redundant nucleotide database, the InterPro domains database, the Gene Ontology Consortium database, and the Kyoto Encyclopedia of Genes and Genomes pathway database. A total of 4,207 unigenes were assigned to specific metabolic pathways, and all of the known enzymes involved in starch and sucrose metabolism pathways were also identified in the KEGG library. This study indicated that alpha-glucan phosphorylase 1, putative pectinesterase/pectinesterase inhibitor 17, beta-amylase, and alpha-glucan phosphorylase isozyme H might be important factors involved in starch and sucrose metabolism between FCG and MCG in different environments.