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Laser Capture Microdissection–Based mRNA Expression Microarrays and Single-Cell RNA Sequencing in Atherosclerosis Research

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Název: Laser Capture Microdissection–Based mRNA Expression Microarrays and Single-Cell RNA Sequencing in Atherosclerosis Research
Autoři: Zhang, Xi, Wang, Zhihua, Zhang, Chuankai, Li, Yutao, Lu, Shu, Steffens, Sabine, Mohanta, Sarajo, Weber, Christian, Habenicht, Andreas, Yin, Changjun
Zdroj: Methods in Molecular Biology ISBN: 9781071619230
Informace o vydavateli: Springer US, 2022.
Rok vydání: 2022
Témata: 0301 basic medicine, 0303 health sciences, Sequence Analysis, RNA, Gene Expression Profiling, Oligonucleotide Array Sequence Analysis/methods, RNA/genetics, Laser Capture Microdissection, Atherosclerosis, 03 medical and health sciences, Atherosclerosis/genetics, Messenger/genetics, Humans, RNA, RNA, Messenger, Gene Expression Profiling/methods, Single-Cell Analysis, Laser Capture Microdissection/methods, Sequence Analysis, Oligonucleotide Array Sequence Analysis
Popis: A major goal of methodologies related to large scale gene expression analyses is to initiate comprehensive information on transcript signatures in single cells within the tissue's anatomy. Until now, this could be achieved in a stepwise experimental approach: (1) identify the majority of transcripts in a single cell (single cell transcriptome); (2) provide information on transcripts on multiple cell subtypes in a complex sample (cell heterogeneity); and (3) give information on each cell's spatial location within the tissue (zonation transcriptomics). Such genetic information will allow construction of functionally relevant gene expression maps of single cells of a given anatomically defined tissue compartment and thus pave the way for subsequent analyses, including their epigenetic modifications. Until today these aims have not been achieved in the area of cardiovascular disease research though steps toward these goals become apparent: laser capture microdissection (LCM)-based mRNA expression microarrays of atherosclerotic plaques were applied to gain information on local gene expression changes during disease progression, providing limited spatial resolution. Moreover, while LCM-derived tissue RNA extracts have been shown to be highly sensitive and covers a range of 10-16,000 genes per array/small amount of RNA, its original promise to isolate single cells from a tissue section turned out not to be practicable because of the inherent contamination of the cell's RNA of interest with RNA from neighboring cells. Many shortcomings of LCM-based analyses have been overcome using single-cell RNA sequencing (scRNA-seq) technologies though scRNA-seq also has several limitations including low numbers of transcripts/cell and the complete loss of spatial information. Here, we describe a protocol toward combining advantages of both techniques while avoiding their flaws.
Druh dokumentu: Part of book or chapter of book
Article
Jazyk: English
DOI: 10.1007/978-1-0716-1924-7_43
Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/35237997
Rights: Springer TDM
Přístupové číslo: edsair.doi.dedup.....d561bac28f124c84ed6b1211fc6272a4
Databáze: OpenAIRE
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  Label: Title
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  Data: Laser Capture Microdissection–Based mRNA Expression Microarrays and Single-Cell RNA Sequencing in Atherosclerosis Research
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  Data: <searchLink fieldCode="AR" term="%22Zhang%2C+Xi%22">Zhang, Xi</searchLink><br /><searchLink fieldCode="AR" term="%22Wang%2C+Zhihua%22">Wang, Zhihua</searchLink><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Chuankai%22">Zhang, Chuankai</searchLink><br /><searchLink fieldCode="AR" term="%22Li%2C+Yutao%22">Li, Yutao</searchLink><br /><searchLink fieldCode="AR" term="%22Lu%2C+Shu%22">Lu, Shu</searchLink><br /><searchLink fieldCode="AR" term="%22Steffens%2C+Sabine%22">Steffens, Sabine</searchLink><br /><searchLink fieldCode="AR" term="%22Mohanta%2C+Sarajo%22">Mohanta, Sarajo</searchLink><br /><searchLink fieldCode="AR" term="%22Weber%2C+Christian%22">Weber, Christian</searchLink><br /><searchLink fieldCode="AR" term="%22Habenicht%2C+Andreas%22">Habenicht, Andreas</searchLink><br /><searchLink fieldCode="AR" term="%22Yin%2C+Changjun%22">Yin, Changjun</searchLink>
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  Data: Methods in Molecular Biology ISBN: 9781071619230
– Name: Publisher
  Label: Publisher Information
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  Data: Springer US, 2022.
– Name: DatePubCY
  Label: Publication Year
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  Data: 2022
– Name: Subject
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  Data: <searchLink fieldCode="DE" term="%220301+basic+medicine%22">0301 basic medicine</searchLink><br /><searchLink fieldCode="DE" term="%220303+health+sciences%22">0303 health sciences</searchLink><br /><searchLink fieldCode="DE" term="%22Sequence+Analysis%2C+RNA%22">Sequence Analysis, RNA</searchLink><br /><searchLink fieldCode="DE" term="%22Gene+Expression+Profiling%22">Gene Expression Profiling</searchLink><br /><searchLink fieldCode="DE" term="%22Oligonucleotide+Array+Sequence+Analysis%2Fmethods%22">Oligonucleotide Array Sequence Analysis/methods</searchLink><br /><searchLink fieldCode="DE" term="%22RNA%2Fgenetics%22">RNA/genetics</searchLink><br /><searchLink fieldCode="DE" term="%22Laser+Capture+Microdissection%22">Laser Capture Microdissection</searchLink><br /><searchLink fieldCode="DE" term="%22Atherosclerosis%22">Atherosclerosis</searchLink><br /><searchLink fieldCode="DE" term="%2203+medical+and+health+sciences%22">03 medical and health sciences</searchLink><br /><searchLink fieldCode="DE" term="%22Atherosclerosis%2Fgenetics%22">Atherosclerosis/genetics</searchLink><br /><searchLink fieldCode="DE" term="%22Messenger%2Fgenetics%22">Messenger/genetics</searchLink><br /><searchLink fieldCode="DE" term="%22Humans%22">Humans</searchLink><br /><searchLink fieldCode="DE" term="%22RNA%22">RNA</searchLink><br /><searchLink fieldCode="DE" term="%22RNA%2C+Messenger%22">RNA, Messenger</searchLink><br /><searchLink fieldCode="DE" term="%22Gene+Expression+Profiling%2Fmethods%22">Gene Expression Profiling/methods</searchLink><br /><searchLink fieldCode="DE" term="%22Single-Cell+Analysis%22">Single-Cell Analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Laser+Capture+Microdissection%2Fmethods%22">Laser Capture Microdissection/methods</searchLink><br /><searchLink fieldCode="DE" term="%22Sequence+Analysis%22">Sequence Analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Oligonucleotide+Array+Sequence+Analysis%22">Oligonucleotide Array Sequence Analysis</searchLink>
– Name: Abstract
  Label: Description
  Group: Ab
  Data: A major goal of methodologies related to large scale gene expression analyses is to initiate comprehensive information on transcript signatures in single cells within the tissue's anatomy. Until now, this could be achieved in a stepwise experimental approach: (1) identify the majority of transcripts in a single cell (single cell transcriptome); (2) provide information on transcripts on multiple cell subtypes in a complex sample (cell heterogeneity); and (3) give information on each cell's spatial location within the tissue (zonation transcriptomics). Such genetic information will allow construction of functionally relevant gene expression maps of single cells of a given anatomically defined tissue compartment and thus pave the way for subsequent analyses, including their epigenetic modifications. Until today these aims have not been achieved in the area of cardiovascular disease research though steps toward these goals become apparent: laser capture microdissection (LCM)-based mRNA expression microarrays of atherosclerotic plaques were applied to gain information on local gene expression changes during disease progression, providing limited spatial resolution. Moreover, while LCM-derived tissue RNA extracts have been shown to be highly sensitive and covers a range of 10-16,000 genes per array/small amount of RNA, its original promise to isolate single cells from a tissue section turned out not to be practicable because of the inherent contamination of the cell's RNA of interest with RNA from neighboring cells. Many shortcomings of LCM-based analyses have been overcome using single-cell RNA sequencing (scRNA-seq) technologies though scRNA-seq also has several limitations including low numbers of transcripts/cell and the complete loss of spatial information. Here, we describe a protocol toward combining advantages of both techniques while avoiding their flaws.
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– Name: Language
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  Data: English
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1007/978-1-0716-1924-7_43
– Name: URL
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  Data: <link linkTarget="URL" linkTerm="https://pubmed.ncbi.nlm.nih.gov/35237997" linkWindow="_blank">https://pubmed.ncbi.nlm.nih.gov/35237997</link>
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  Data: edsair.doi.dedup.....d561bac28f124c84ed6b1211fc6272a4
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        Value: 10.1007/978-1-0716-1924-7_43
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      – Text: English
    Subjects:
      – SubjectFull: 0301 basic medicine
        Type: general
      – SubjectFull: 0303 health sciences
        Type: general
      – SubjectFull: Sequence Analysis, RNA
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      – SubjectFull: Gene Expression Profiling
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      – SubjectFull: Laser Capture Microdissection
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      – SubjectFull: Atherosclerosis
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      – SubjectFull: 03 medical and health sciences
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      – SubjectFull: Atherosclerosis/genetics
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      – SubjectFull: Oligonucleotide Array Sequence Analysis
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      – TitleFull: Laser Capture Microdissection–Based mRNA Expression Microarrays and Single-Cell RNA Sequencing in Atherosclerosis Research
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