检索结果-南通市图书馆

multi‑omics integration identifies regulatory factors underlying bovine subclinical mastitis

Journal of Animal Science and Biotechnology 2024年第3期15卷 987-1007页

作者： Mengqi Wang Naisu Yang Mario Laterriere David Gagne Faith Omonijo Eveline M.Ibeagha‑Awemu Agriculture and Agri‑Food Canada Sherbrooke Research and Development CentreSherbrookeQCCanada Department of Animal Science Universite LavalQuebec CityQCCanada Quebec Research and Development Centre Agriculture and Agri-Food CanadaQuebec CityQCCanada

Background Mastitis caused by multiple factors remains one of the most common and costly disease of the dairy industry.multi-omics approaches enable the comprehensive investigation of the complex interactions between mul-tiple layers of information to provide a more holistic view of disease pathogenesis.Therefore,this study investigated the genomic and epigenomic signatures and the possible regulatory mechanisms underlying subclinical mastitis by integrating RNA sequencing data(mRNA and lncRNA),small RNA sequencing data(miRNA)and DNA methylation sequencing data of milk somatic cells from 10 healthy cows and 20 cows with naturally occurring subclinical mastitis caused by Staphylococcus aureus or Staphylococcus chromogenes.Results Functional investigation of the data sets through gene set analysis uncovered 3458 biological process GO terms and 170 KEGG pathways with altered activities during subclinical mastitis,provided further insights into subclin-ical mastitis and revealed the involvement of multi-omics signatures in the altered immune responses and impaired mammary gland productivity during subclinical mastitis.The abundant genomic and epigenomic signatures with sig-nificant alterations related to subclinical mastitis were observed,including 30,846,2552,1276 and 57 differential methylation haplotype blocks(dMHBs),differentially expressed genes(DEGs),lncRNAs(DELs)and miRNAs(DEMs),respectively.Next,5 factors presenting the principal variation of differential multi-omics signatures were identified.The important roles of Factor 1(DEG,DEM and DEL)and Factor 2(dMHB and DEM),in the regulation of immune defense and impaired mammary gland functions during subclinical mastitis were revealed.Each of the omics within Factors 1 and 2 explained about 20%of the source of variation in subclinical mastitis.Also,networks of impor-tant functional gene sets with the involvement of multi-omics signatures were demonstrated,which contributed to a comprehensive view of the possible regulatory mechanisms underlying subclinical mastiti

关键词： Candidate discriminant multi-omics signature Gene Long non-coding RNA Methylation haplotype block MicroRNA multi-omics integration Natural killer cell mediated cytotoxicity pathway Staphylococcus aureus infection pathway

来源：

维普期刊数据库

同方期刊数据库博看期刊评论

在线全文

学校读者我要写书评

暂无评论

omics approaches in asthma research:Challenges and opportunities

引用

Chinese Medical Journal Pulmonary and Critical Care Medicine 2024年第1期2卷 1-9页

作者： Molin Yue Shiyue Tao Kristina Gaietto Wei Chen Department of Biostatistics School of Public HealthUniversity of PittsburghPittsburghPA 15224USA Division of Pediatric Pulmonary Medicine UPMC Children’s Hospital of PittsburghUniversity of PittsburghPittsburghPA 15224USA

Asthma,a chronic respiratory disease with a global prevalence of approximately 300 million individuals,presents a significant societal and economic burden.This multifaceted syndrome exhibits diverse clinical phenotypes and pathogenic endotypes influenced by various factors.The advent of omics technologies has revolutionized asthma research by delving into the molecular foundation of the disease to unravel its underlying mechanisms.omics technologies are employed to systematically screen for potential biomarkers,encompassing genes,transcripts,methylation sites,proteins,and even the microbiome components.This review provides an insightful overview of omics applications in asthma research,with a special emphasis on genetics,transcriptomics,epigenomics,and the microbiome.We explore the cutting-edge methods,discoveries,challenges,and potential future directions in the realm of asthma omics research.By integrating multi-omics and non-omics data through advanced sta-tistical techniques,we aspire to advance precision medicine in asthma,guiding diagnosis,risk assessment,and personalized treatment strategies for this heterogeneous condition.

关键词： Asthma Genomics Transcriptomics Epigenomics Metagenomics multi-omics integration

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computational Approaches and Challenges in Spatial Transcriptomics

引用

Genomics, Proteomics & Bioinformatics 2023年第1期21卷 24-47页

作者： Shuangsang Fang Bichao Chen Yong Zhang Haixi Sun Longqi Liu Shiping Liu Yuxiang Li Xun Xu BGI-Shenzhen Shenzhen 518083China BGI-Beijing Beijing 100101China Guangdong Bigdata Engineering Technology Research Center for Life Sciences Shenzhen 518083China

The development of spatial transcriptomics(ST)technologies has transformed genetic research from a single-cell data level to a two-dimensional spatial coordinate system and facilitated the study of the composition and function of various cell subsets in different environments and organs.The large-scale data generated by these ST technologies,which contain spatial gene expression information,have elicited the need for spatially resolved approaches to meet the requirements of computational and biological data interpretation.These requirements include dealing with the explosive growth of data to determine the cell-level and gene-level expression,correcting the inner batch effect and loss of expression to improve the data quality,conducting efficient interpretation and in-depth knowledge mining both at the single-cell and tissue-wide levels,and conducting multi-omics integration analysis to provide an extensible framework toward the in-depth understanding of biological processes.However,algorithms designed specifically for ST technologies to meet these requirements are still in their infancy.Here,we review computational approaches to these problems in light of corresponding issues and challenges,and present forward-looking insights into algorithm development.

关键词： Spatial transcriptomics Computational approach Data quality Data interpretation multi-omics integration

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Integrative multi-omics and systems bioinformatics in translational neuroscience:A data mining perspective

引用

药物分析学报:英文版 2023年第8期13卷 836-850页

作者： Lance M.O'Connor Blake A.O'Connor Su Bin Lim Jialiu Zeng Chih Hung Lo College of Biological Sciences University of MinnesotaMinneapolisMN55455USA School of Pharmacy University of WisconsinMadisonWI53705USA Department of Biochemistry and Molecular Biology Ajou University School of MedicineSuwon16499South Korea Lee Kong Chian School of Medicine Nanyang Technological UniversitySingapore308232Singapore

Bioinformatic analysis of large and complex omics datasets has become increasingly useful in modern day biology by providing a great depth of information,with its application to neuroscience termed neuroinformatics.Data mining of omics datasets has enabled the generation of new hypotheses based on differentially regulated biological molecules associated with disease mechanisms,which can be tested experimentally for improved diagnostic and therapeutic targeting of neurodegenerative diseases.Importantly,integrating multi-omics data using a systems bioinformatics approach will advance the understanding of the layered and interactive network of biological regulation that exchanges systemic knowledge to facilitate the development of a comprehensive human brain profile.In this review,we first summarize data mining studies utilizing datasets from the individual type of omics analysis,including epigenetics/epigenomics,transcriptomics,proteomics,metabolomics,lipidomics,and spatial omics,pertaining to Alzheimer's disease,Parkinson's disease,and multiple sclerosis.We then discuss multi-omics integration approaches,including independent biological integration and unsupervised integration methods,for more intuitive and informative interpretation of the biological data obtained across different omics layers.We further assess studies that integrate multi-omics in data mining which provide convoluted biological insights and offer proof-of-concept proposition towards systems bioinformatics in the reconstruction of brain networks.Finally,we recommend a combination of high dimensional bioinformatics analysis with experimental validation to achieve translational neuroscience applications including biomarker discovery,therapeutic development,and elucidation of disease mechanisms.We conclude by providing future perspectives and opportunities in applying integrative multi-omics and systems bioinformatics to achieve precision phenotyping of neurodegenerative diseases and towards personalized medicine.

关键词： multi-omics integration Systems bioinformatics Data mining Human brain profile reconstruction Translational neuroscience

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

multi-omics Analysis of Young Portulaca oleracea L.Plants’Responses to High NaCl Doses Reveals Insights into Pathways and Genes Responsive to Salinity Stress in this Halophyte Species

引用

Phenomics 2023年第1期3卷 1-21页

作者： Vivianny Nayse Belo Silva Thalliton Luiz Carvalho da Silva Thalita Massaro Malheiros Ferreira Jorge Candido Rodrigues Neto AndréPereira Leão JoséAntônio de Aquino Ribeiro Patrícia Verardi Abdelnur Leonardo Fonseca Valadares Carlos Antônio Ferreira de Sousa Manoel Teixeira Souza Júnior Graduate Program of Plant Biotechnology Federal University of LavrasCP 3037LavrasMG 37200-000Brazil Institute of Chemistry Federal University of GoiásCampus SamambaiaGoiâniaGO 74690‐900Brazil Brazilian Agricultural Research Corporation Embrapa Mid-NorthTeresinaPI 64008-780Brazil Brazilian Agricultural Research Corporation Embrapa AgroenergyBrasíliaDF 70770‐901Brazil

Soil salinity is among the abiotic stressors that threaten agriculture the most,and purslane(Portulaca oleracea L.)is a dicot species adapted to inland salt desert and saline habitats that hyper accumulates salt and has high phytoremediation potential.Many researchers consider purslane a suitable model species to study the mechanisms of plant tolerance to drought and salt stresses.Here,a robust salinity stress protocol was developed and used to characterize the morphophysiological responses of young purslane plants to salinity stress;then,leaf tissue underwent characterization by distinct omics platforms to gain further insights into its response to very high salinity stress.The salinity stress protocol did generate different levels of stress by gradients of electrical conductivity at field capacity and water potential in the saturation extract of the substrate,and the morphological parameters indicated three distinct stress levels.As expected from a halophyte species,these plants remained alive under very high levels of salinity stress,showing salt crystal-like structures constituted mainly by Na^(+),Cl^(−),and K^(+)on and around closed stomata.A comprehensive and large-scale metabolome and transcriptome single and integrated analyses were then employed using leaf samples.The multi-omics integration(MOI)system analysis led to a data-set of 51 metabolic pathways with at least one enzyme and one metabolite differentially expressed due to salinity stress.These data sets(of genes and metabolites)are valuable for future studies aimed to deepen our knowledge on the mechanisms behind the high tolerance of this species to salinity stress.In conclusion,besides showing that this species applies salt exclusion already in young plants to support very high levels of salinity stress,the initial analysis of metabolites and transcripts data sets already give some insights into other salt tolerance mechanisms used by this species to support high levels of salinity stress.

关键词： Purslane RNA-Seq Chemometrics High-resolution mass spectrometry Abiotic stress multi-omics integration

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

SSIG: Single-Sample Information Gain Model for Integrating multi-omics Data to Identify Cancer Subtypes

引用

Chinese Journal of Electronics 2021年第2期30卷 303-312页

作者： ZHANG Yuanyuan WANG Ziqi WANG Shudong KOU Chuanhua School of Information and Control Engineering Qingdao University of Technology College of Computer Science and Technology China University of Petroleum (East China)

Different living environments of cancer samples lead to different molecular mechanisms of cancer development, which in turn leads to different cancer subtypes. How to identify cancer subtypes is a key issue for the realization of precision medicine. With the development of high-throughput technologies, multi-omics data which can better understand different causes of cancer have emerged. However, the current methods of analyzing cancer subtypes using multi-omics data is mostly derived from population cancer sample data and ignores the differences between different cancer samples.Therefore, the joint analysis of multi-omics based on a single sample may reveal more information about the differences between individual cancers. A strategy for identifying cancer subtypes is proposed based on Single-sample information gain(SSIG) which construct sample feature matrix by considering the heterogeneity of sample. Applying this strategy to current popular subtype identification methods, cancer subtypes can be identified more accurately and the mechanism of cancer can be found from the perspective of a single sample. By comparing different methods in different clustering measure, and using survival analysis, it is shown that SSIG is more suitable for cancer subtype identification than the original multi-omics data, and it is easier to mine the cancer subtype classification mechanism hidden behind the data.

关键词： Cancer subtype multi-omics integration Single-sample information gain

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：