• 제목/요약/키워드: transcriptomics analysis

검색결과 35건 처리시간 0.021초

Deciphering Key Genes of Proliferative and Secretory Phase Using Integrated Transcriptomics and Network Analysis

  • Payal Gupta;Shriya Dube;Payal Priyadarshini;Shanvi Singh;Anasuya Pravallika R;Vijay Lakshmi Srivastava;Abhishek Sengupta;Priyanka Narad
    • 한국미생물·생명공학회지
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    • 제51권3호
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    • pp.317-324
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    • 2023
  • Endometrium receptivity is a complex mechanism of intricate pathways that lead to the shift from the proliferative to the secretory phase. Our goal was to identify high-ranking differentially expressed genes and study the pathways associated with the phenomenon. Raw data were retrieved from six GEO datasets and 705 DEGs were identified through robust ranking aggregation after the integration of five datasets. 20 key genes were identified that were further re-validated in an additional dataset. Supporting evidence through the experimental references confirms them as major biomarkers of the shift from the proliferative to the secretory phase.

Single-cell and spatial transcriptomics approaches of cardiovascular development and disease

  • Roth, Robert;Kim, Soochi;Kim, Jeesu;Rhee, Siyeon
    • BMB Reports
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    • 제53권8호
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    • pp.393-399
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    • 2020
  • Recent advancements in the resolution and throughput of single-cell analyses, including single-cell RNA sequencing (scRNA-seq), have achieved significant progress in biomedical research in the last decade. These techniques have been used to understand cellular heterogeneity by identifying many rare and novel cell types and characterizing subpopulations of cells that make up organs and tissues. Analysis across various datasets can elucidate temporal patterning in gene expression and developmental cues and is also employed to examine the response of cells to acute injury, damage, or disruption. Specifically, scRNA-seq and spatially resolved transcriptomics have been used to describe the identity of novel or rare cell subpopulations and transcriptional variations that are related to normal and pathological conditions in mammalian models and human tissues. These applications have critically contributed to advance basic cardiovascular research in the past decade by identifying novel cell types implicated in development and disease. In this review, we describe current scRNA-seq technologies and how current scRNA-seq and spatial transcriptomic (ST) techniques have advanced our understanding of cardiovascular development and disease.

식품 미생물 균총 연구를 위한 최신 마이크로바이옴 분석 기술 (Recent next-generation sequencing and bioinformatic analysis methods for food microbiome research)

  • 권준기;김선균;이주훈
    • 식품과학과 산업
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    • 제52권3호
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    • pp.220-228
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    • 2019
  • Rapid development of next-generation sequencing (NGS) technology is available to study microbes in genomic level. This NGS has been widely used in DNA/RNA sequencing for genome sequencing, metagenomics, and transcriptomics. The food microbiology area could be categorized into three groups. Food microbes including probiotics and food-borne pathogens are studied in genomic level using NGS for microbial genomics. While food fermentation or food spoilage are more complicated, their genomic study needs to be done with metagenomics using NGS for compositional analysis. Furthermore, because microbial response in food environments are also important to understand their roles in food fermentation or spoilage, pattern analysis of RNA expression in the specific food microbe is conducted using RNA-Seq. These microbial genomics, metagenomics, and transcriptomics for food fermentation and spoilage would extend our knowledge on effective utilization of fermenting bacteria for health promotion as well as efficient control of food-borne pathogens for food safety.

Recent advances in spatially resolved transcriptomics: challenges and opportunities

  • Lee, Jongwon;Yoo, Minsu;Choi, Jungmin
    • BMB Reports
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    • 제55권3호
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    • pp.113-124
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    • 2022
  • Single-cell RNA sequencing (scRNA-seq) has greatly advanced our understanding of cellular heterogeneity by profiling individual cell transcriptomes. However, cell dissociation from the tissue structure causes a loss of spatial information, which hinders the identification of intercellular communication networks and global transcriptional patterns present in the tissue architecture. To overcome this limitation, novel transcriptomic platforms that preserve spatial information have been actively developed. Significant achievements in imaging technologies have enabled in situ targeted transcriptomic profiling in single cells at single-molecule resolution. In addition, technologies based on mRNA capture followed by sequencing have made possible profiling of the genome-wide transcriptome at the 55-100 ㎛ resolution. Unfortunately, neither imaging-based technology nor capture-based method elucidates a complete picture of the spatial transcriptome in a tissue. Therefore, addressing specific biological questions requires balancing experimental throughput and spatial resolution, mandating the efforts to develop computational algorithms that are pivotal to circumvent technology-specific limitations. In this review, we focus on the current state-of-the-art spatially resolved transcriptomic technologies, describe their applications in a variety of biological domains, and explore recent discoveries demonstrating their enormous potential in biomedical research. We further highlight novel integrative computational methodologies with other data modalities that provide a framework to derive biological insight into heterogeneous and complex tissue organization.

바이오 디지털 콘텐츠를 이용한 독성의 분석 (Analysis of toxicity using bio-digital contents)

  • 강진석
    • 디지털콘텐츠학회 논문지
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    • 제11권1호
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    • pp.99-104
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    • 2010
  • 화학물질은 생체에 들어오면 여러 가지 독성반응을 나타내는데, 독성반응에 따른 유전자 발현을 분석하기 위해 바이오 칩 등을 이용한 신기술이 확산되면서 바이오 디지털 콘텐츠가 다량으로 생성되고 있다. 이 콘텐츠는 그 자체로는 의미가 적고 컴퓨터를 이용한 분석과 보정과정을 거쳐 생물학적으로 의미 있는 값들을 선별하여야 한다. 이런 콘텐츠에는 유전자들의 발현 양상 측정을 목적으로 하는 유전체학(genomics), 유전자의 발현 양상을 측정하는 전사체학(transcriptomics), 단백질의 발현을 측정하는 단백체학(proteomics), 대사체의 발현을 측정하는 대사체학(metabolomics) 등이 있으며, 이를 통칭하여 오믹스(omics)라고 부른다. 오믹스 기술을 독성을 연구하는 분야에 접목한 것이 독성유전체학(toxicogenomics)이며, 이에 대한 콘텐츠를 분석함으로써 독성을 예측하고 독성기전을 규명할 수 있다. 독성분석에 있어서 초기 단계의 분석은 향후 만성독성의 예측에 있어서 중요한 부분을 차지하고 있다. 바이오 디지털 콘텐츠를 이용하여 독성을 예측함에 있어 기존의 방법보다 더 빠르고 정확하게 예측하기 위해서는 많은 정보에 대한 분석기술의 진보가 필요하다. 또, 바이오 디지털 콘텐츠를 이용한 독성예측에 있어서 전체세포보다는 생물학적 현상을 일으키는 특이세포에서 이런 정보를 얻는 것이 중요하다고 생각된다. 또, 향후 바이오 디지털 콘텐츠 분석은 전략적 실험설계에 의한 데이터가 분석되고 축적되어야 하고, 분석알고리즘을 통한 네트워크 분석이 이루어져야 하며, 통합적 데이터 구축을 통해 이루어져야 할 것으로 생각된다.

Integrative Omics Reveals Metabolic and Transcriptomic Alteration of Nonalcoholic Fatty Liver Disease in Catalase Knockout Mice

  • Na, Jinhyuk;Choi, Soo An;Khan, Adnan;Huh, Joo Young;Piao, Lingjuan;Hwang, Inah;Ha, Hunjoo;Park, Youngja H
    • Biomolecules & Therapeutics
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    • 제27권2호
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    • pp.134-144
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    • 2019
  • The prevalence of nonalcoholic fatty liver disease (NAFLD) has increased with the incidence of obesity; however, the underlying mechanisms are unknown. In this study, high-resolution metabolomics (HRM) along with transcriptomics were applied on animal models to draw a mechanistic insight of NAFLD. Wild type (WT) and catalase knockout (CKO) mice were fed with normal fat diet (NFD) or high fat diet (HFD) to identify the changes in metabolic and transcriptomic profiles caused by catalase gene deletion in correspondence with HFD. Integrated omics analysis revealed that cholic acid and $3{\beta}$, $7{\alpha}$-dihydroxy-5-cholestenoate along with cyp7b1 gene involved in primary bile acid biosynthesis were strongly affected by HFD. The analysis also showed that CKO significantly changed all-trans-5,6-epoxy-retinoic acid or all-trans-4-hydroxy-retinoic acid and all-trans-4-oxo-retinoic acid along with cyp3a41b gene in retinol metabolism, and ${\alpha}/{\gamma}$-linolenic acid, eicosapentaenoic acid and thromboxane A2 along with ptgs1 and tbxas1 genes in linolenic acid metabolism. Our results suggest that dysregulated primary bile acid biosynthesis may contribute to liver steatohepatitis, while up-regulated retinol metabolism and linolenic acid metabolism may have contributed to oxidative stress and inflammatory phenomena in our NAFLD model created using CKO mice fed with HFD.

복숭아 유전체 및 전사체 최근 연구 동향 (Current status of peach genomics and transcriptomics research)

  • 조강희;권정현;김세희;전지혜
    • Journal of Plant Biotechnology
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    • 제42권4호
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    • pp.312-325
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    • 2015
  • 본 논문에서는 장미과 과수의 유전체 연구의 모델작물인 복숭아 유전체 연구에 대한 동향을 파악해서 국내 복숭아 유전체 연구 방향을 설정하고자 하였다. 분자육종을 위한 기반 연구인 유전자지도는 다양한 교배집단에서 작성되었고, 현재 차세대 염기서열분석을 통해 얻은 대량의 single nucleotide polymorphism 마커를 이용하여 고밀도화시키고 있다. 과실형질, 개화기, 병 저항성 등 질적형질과 양적형질에 관한 분자마커와 양적형질유전자좌가 동정되었고, 이중 과육의 용질성과 핵의 점리 형질에 대한 분자마커를 이용한 조기선발(marker assisted selection)의 활용성은 매우 높다. 애기장대, 포플라, 사과, 딸기 등 다른 작물과의 비교유전체, 복숭아의 성숙 및 발달, 플라보노이드 합성, 수확 후 저장기간에 발현하는 유전자 등에 대한 전사체, 과실 성숙기간에 발현되는 병 저항성 단백질 등에 대한 단백질체 연구도 보고되었다. 현재 차세대 염기서열 분석을 통해 대량 분자마커의 개발, 핵심 유전자원의 구축, 집단의 유전형 분석이 빠르게 진행되고 있다. 이를 통해 농업적으로 유용한 형질에 대해 더 정확한 양적형질 유전자좌 분석과 유용유전자의 개발이 가능하게 되고, 효율적인 분자육종의 기초기반을 구축할 수 있을 것으로 기대한다.

Advances in Systems Biology Approaches for Autoimmune Diseases

  • Kim, Ho-Youn;Kim, Hae-Rim;Lee, Sang-Heon
    • IMMUNE NETWORK
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    • 제14권2호
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    • pp.73-80
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    • 2014
  • Because autoimmune diseases (AIDs) result from a complex combination of genetic and epigenetic factors, as well as an altered immune response to endogenous or exogenous antigens, systems biology approaches have been widely applied. The use of multi-omics approaches, including blood transcriptomics, genomics, epigenetics, proteomics, and metabolomics, not only allow for the discovery of a number of biomarkers but also will provide new directions for further translational AIDs applications. Systems biology approaches rely on high-throughput techniques with data analysis platforms that leverage the assessment of genes, proteins, metabolites, and network analysis of complex biologic or pathways implicated in specific AID conditions. To facilitate the discovery of validated and qualified biomarkers, better-coordinated multi-omics approaches and standardized translational research, in combination with the skills of biologists, clinicians, engineers, and bioinformaticians, are required.

식물 생명공학과 생물정보학 (Plant Biotechnology and Bioinformatics)

  • 김정은;백효정;김영철;허철구
    • Journal of Plant Biotechnology
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    • 제33권3호
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    • pp.209-222
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    • 2006
  • 애기 장대와 벼의 전체 게놈 염기서열 분석이 완료되었고, 다량의 EST 데이터가 많은 식물에서 이용 가능하게 되었다. 또한, 방대한 양의 다양한 생물학적 데이터들이 transcriptomics, proteomics, metabolomics와 같은 여러 '-omics' 기술에 의하여 만들어져 왔다. 생물정보학은 이런 방대한 양의 생물학적 데이터로부터 유용한 정보를 얻는데 필수적이고도 매우 중요한 역할을 수행한다. 이 총설에서, 우리는 대량의 데이터를 생성하는 실험적 방법들과, 식물 병 저항성과 분자 육종과 같은 식물 연구분야로의 응용, 그리고 식물 생명공학의 연구 개발에 유용한 생물정보학적 기술과. 인터넷 정보 사이트들을 소개하였다. 우리는 새로운 실험 방법들과 생물정보학적 분석 기술들이 식물 생명공학 발전에 중요하게 기여할 것으로 기대하고 있으며, 생물정보학은 식물 생명공학의 연구 개발에 있어서 결정적인 요소가 될 것이라 생각한다.

전사체 프로파일을 이용한 고려 홍삼의 항당뇨 기전 연구 (Anti-diabetic Mechannism Study of Korean Red Ginseng by Transcriptomics)

  • 원해단;신은정;정성현
    • 약학회지
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    • 제52권5호
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    • pp.345-354
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    • 2008
  • This study was designed to investigate the anti-diabetic effect and mechanism of Korean red ginseng extract through transcriptomics in C57BL/KsJ db/db mice. The db/db mice were randomly divided into six groups: diabetic control group (DC), red ginseng extract low dose group (RGL, 100 mg/kg), red ginseng extract high dose group (RGH, 200 mg/kg), metformin group (MET, 300 mg/kg), glipizide group (GPZ, 15 mg/kg) and pioglitazone group (PIO, 30 mg/kg), and treated with drugs once per day for 10 weeks. At the end of treatment, we measured blood glucose, insulin, hemoglobin A1c (HbA1c), triglyceride (TG), adiponectin, leptin, non-esterified fatty acid (NEFA). RGL-treated group lowered the blood glucose and HbA1c levels by 19.6% and 11.4% compared to those in diabetic control group. In addition, plasma adiponectin and leptin levels in RGL-treated groups were increased by 20% and 12%, respectively, compared to those in diabetic control. Morphological analyses of liver, pancreas and epidydimal adipose tissue were done by hematoxylin-eosin staining, and pancreatic islet insulin and glucagon levels were detected by double-immunofluorescence staining. RGL-treated group revealed higher insulin contents and lower glucagon contents compared to diabetic control. To elucidate an action mechanism of Korean red ginseng, DNA microarray analyses were performed in liver and fat tissues, and western blot and RT-PCR were conducted in liver for validation. According to hierarchical clustering and principal component analysis of gene expression Korean red ginseng treated groups were close to metformin treated group. In summary, Korean red ginseng lowered the blood glucose level through protecting destruction of islet cells and shifting glucose metabolism from hepatic glucose production to glucose utilization and improving insulin sensitivity through enhancing plasma adiponectin and leptin levels.