{"title":"多层分析阿尔茨海默病的 RNA 测序数据,揭开分子奥秘。","authors":"Dilara Uzuner, Atılay İlgün, Elif Düz, Fatma Betül Bozkurt, Tunahan Çakır","doi":"10.1007/978-3-031-69188-1_9","DOIUrl":null,"url":null,"abstract":"<p><p>Alzheimer's disease (AD) is a complex disease, and numerous cellular events may be involved in etiology. RNAseq-based transcriptome data hold multilayer information content, which could be crucial in unraveling molecular mysteries of AD. It enables quantification of gene expression levels, identification of genomic variants, and elucidation of splicing anomalies such as exon skipping and intron retention. Additional integration of this information into protein-protein interaction networks and genome-scale metabolic models from the literature has potential to decipher functional modules and affected mechanisms for complex scenarios such as AD. In this chapter, we review the application areas of the multilayer content of RNAseq and associated integrative approaches available, with a special focus on AD.</p>","PeriodicalId":7360,"journal":{"name":"Advances in neurobiology","volume":"41 ","pages":"219-246"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multilayer Analysis of RNA Sequencing Data in Alzheimer's Disease to Unravel Molecular Mysteries.\",\"authors\":\"Dilara Uzuner, Atılay İlgün, Elif Düz, Fatma Betül Bozkurt, Tunahan Çakır\",\"doi\":\"10.1007/978-3-031-69188-1_9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Alzheimer's disease (AD) is a complex disease, and numerous cellular events may be involved in etiology. RNAseq-based transcriptome data hold multilayer information content, which could be crucial in unraveling molecular mysteries of AD. It enables quantification of gene expression levels, identification of genomic variants, and elucidation of splicing anomalies such as exon skipping and intron retention. Additional integration of this information into protein-protein interaction networks and genome-scale metabolic models from the literature has potential to decipher functional modules and affected mechanisms for complex scenarios such as AD. In this chapter, we review the application areas of the multilayer content of RNAseq and associated integrative approaches available, with a special focus on AD.</p>\",\"PeriodicalId\":7360,\"journal\":{\"name\":\"Advances in neurobiology\",\"volume\":\"41 \",\"pages\":\"219-246\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in neurobiology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/978-3-031-69188-1_9\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Neuroscience\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in neurobiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/978-3-031-69188-1_9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Neuroscience","Score":null,"Total":0}
引用次数: 0
摘要
阿尔茨海默病(AD)是一种复杂的疾病,病因可能涉及众多细胞事件。基于 RNAseq 的转录组数据蕴含着多层次的信息内容,对于揭开阿尔茨海默病的分子奥秘至关重要。它可以量化基因表达水平,鉴定基因组变异,阐明剪接异常,如外显子跳过和内含子保留。将这些信息与蛋白质-蛋白质相互作用网络和文献中的基因组规模代谢模型进一步整合,有可能破译功能模块和影响 AD 等复杂情况的机制。在本章中,我们将回顾 RNAseq 多层内容的应用领域以及相关的整合方法,并特别关注注意力缺失症。
Multilayer Analysis of RNA Sequencing Data in Alzheimer's Disease to Unravel Molecular Mysteries.
Alzheimer's disease (AD) is a complex disease, and numerous cellular events may be involved in etiology. RNAseq-based transcriptome data hold multilayer information content, which could be crucial in unraveling molecular mysteries of AD. It enables quantification of gene expression levels, identification of genomic variants, and elucidation of splicing anomalies such as exon skipping and intron retention. Additional integration of this information into protein-protein interaction networks and genome-scale metabolic models from the literature has potential to decipher functional modules and affected mechanisms for complex scenarios such as AD. In this chapter, we review the application areas of the multilayer content of RNAseq and associated integrative approaches available, with a special focus on AD.