Time course analysis of large-scale gene expression in incised muscle using correspondence analysis
Studying the time course of gene expression in injured skeletal muscle would help to estimate the timing of injuries. In this study, we investigated large-scale gene expression in incision-injured mouse skeletal muscle by DNA microarray using correspondence analysis (CA). Biceps femoris muscle sampl...
Gespeichert in:
| Veröffentlicht in: | PloS one 2020-03, Vol.15 (3), p.e0230737-e0230737 |
|---|---|
| Hauptverfasser: | , , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | e0230737 |
|---|---|
| container_issue | 3 |
| container_start_page | e0230737 |
| container_title | PloS one |
| container_volume | 15 |
| creator | Horita, Tetsuya Gaballah, Mohammed Hassan Fukuta, Mamiko Kanno, Sanae Kato, Hideaki Takamiya, Masataka Aoki, Yasuhiro |
| description | Studying the time course of gene expression in injured skeletal muscle would help to estimate the timing of injuries. In this study, we investigated large-scale gene expression in incision-injured mouse skeletal muscle by DNA microarray using correspondence analysis (CA). Biceps femoris muscle samples were collected 6, 12, and 24 hours after injury, and RNA was extracted and prepared for microarray analysis. On a 2-dimensional plot by CA, the genes (row score coordinate) located farther from each time series (column score coordinate) had more upregulation at particular times. Each gene was situated in 6 subdivided triangular areas according to the magnitude of the relationship of the fold change (FC) value at each time point compared to the control. In each area, genes for which the ratios of two particular FC values were close to 1 were distributed along the two border lines. There was a tendency for genes whose FC values were almost equal to be distributed near the intersection of these 6 areas. Therefore, the gene marker candidates for estimation of the timing of injuries were detectable according to the location on the CA plot. Moreover, gene sets created by a specific gene and its surrounding genes were composed of genes that showed similar or identical fluctuation patterns to the specific gene. In various analyses on these sets, significant gene ontology term and pathway activity may reflect changes in specific genes. In conclusion, analyses of gene sets based on CA plots is effective for investigation of the time-dependent fluctuation in gene expression after injury. |
| doi_str_mv | 10.1371/journal.pone.0230737 |
| format | Article |
| fullrecord | <record><control><sourceid>gale_plos_</sourceid><recordid>TN_cdi_plos_journals_2382996197</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A618524006</galeid><doaj_id>oai_doaj_org_article_9c23de9d45ff49feaa2c1ec941a825ad</doaj_id><sourcerecordid>A618524006</sourcerecordid><originalsourceid>FETCH-LOGICAL-c692t-17e1abb53a0fd841be5ded08ea0dd6d927254d0c54376b8b47996df380aa727f3</originalsourceid><addsrcrecordid>eNqNk99r1TAUgIsobk7_A9GCIPpwr_nZNC_CGFMvDAY6fQ1pctqbS9tck1a2_365u928lT1ICw3pd74kJ-dk2WuMlpgK_Gnjx9Drdrn1PSwRoUhQ8SQ7xpKSRUEQfXowPspexLhBiNOyKJ5nR5QQjBhnx5m5ch3kJrki5Dr5bqKLua_zVocGFtHoFvIGesjhehsgRuf73O1e4yLYvBujScQYXd8kTUhI2pCF3vzVvcye1bqN8Gr6nmQ_v5xfnX1bXFx-XZ2dXixMIcmwwAKwripONaptyXAF3IJFJWhkbWElEYQziwxnVBRVWTEhZWFrWiKtBRE1Pcne7r3b1kc15ScqQkuSSCxFIlZ7wnq9UdvgOh1ulNdO3U340CgdBpdOpKQh1IK0jNc1kzVoTQwGIxnWJeHaJtfnabWx6sAa6Ieg25l0_qd3a9X4P0ogyUrOk-DDJAj-9whxUJ2LBtpW9-DHu31TjgvOUULf_YM-frqJatKlKdfXPq1rdlJ1WuCSE4ZQkajlI1R6LHTOpGKqXZqfBXycBSRmgOuh0WOMavXj-_-zl7_m7PsDdg26HdbRt-OQSizOQbYHTfAxBqgfkoyR2vXCfTbUrhfU1Asp7M3hBT0E3Rc_vQWGEAW_</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2382996197</pqid></control><display><type>article</type><title>Time course analysis of large-scale gene expression in incised muscle using correspondence analysis</title><source>PLoS</source><source>DOAJ Directory of Open Access Journals</source><source>PubMed Central</source><source>Free Full-Text Journals in Chemistry</source><source>EZB Electronic Journals Library</source><creator>Horita, Tetsuya ; Gaballah, Mohammed Hassan ; Fukuta, Mamiko ; Kanno, Sanae ; Kato, Hideaki ; Takamiya, Masataka ; Aoki, Yasuhiro</creator><contributor>Du, Shao Jun</contributor><creatorcontrib>Horita, Tetsuya ; Gaballah, Mohammed Hassan ; Fukuta, Mamiko ; Kanno, Sanae ; Kato, Hideaki ; Takamiya, Masataka ; Aoki, Yasuhiro ; Du, Shao Jun</creatorcontrib><description>Studying the time course of gene expression in injured skeletal muscle would help to estimate the timing of injuries. In this study, we investigated large-scale gene expression in incision-injured mouse skeletal muscle by DNA microarray using correspondence analysis (CA). Biceps femoris muscle samples were collected 6, 12, and 24 hours after injury, and RNA was extracted and prepared for microarray analysis. On a 2-dimensional plot by CA, the genes (row score coordinate) located farther from each time series (column score coordinate) had more upregulation at particular times. Each gene was situated in 6 subdivided triangular areas according to the magnitude of the relationship of the fold change (FC) value at each time point compared to the control. In each area, genes for which the ratios of two particular FC values were close to 1 were distributed along the two border lines. There was a tendency for genes whose FC values were almost equal to be distributed near the intersection of these 6 areas. Therefore, the gene marker candidates for estimation of the timing of injuries were detectable according to the location on the CA plot. Moreover, gene sets created by a specific gene and its surrounding genes were composed of genes that showed similar or identical fluctuation patterns to the specific gene. In various analyses on these sets, significant gene ontology term and pathway activity may reflect changes in specific genes. In conclusion, analyses of gene sets based on CA plots is effective for investigation of the time-dependent fluctuation in gene expression after injury.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0230737</identifier><identifier>PMID: 32210454</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Analysis ; Biochemistry ; Biology and Life Sciences ; Cell cycle ; Cytokines ; Deoxyribonucleic acid ; DNA ; DNA chips ; DNA microarrays ; Flags ; Forensic medicine ; Forensic pathology ; Gene expression ; Genes ; Genetic aspects ; Genetic markers ; Injuries ; Injury analysis ; Laboratory animals ; Medicine and Health Sciences ; Muscles ; Musculoskeletal system ; Ontology ; Principal components analysis ; Quality control ; Research and Analysis Methods ; Ribonucleic acid ; RNA ; Skeletal muscle ; Skin ; Time ; Time dependence ; Two dimensional analysis ; University graduates ; Values ; Variance analysis</subject><ispartof>PloS one, 2020-03, Vol.15 (3), p.e0230737-e0230737</ispartof><rights>COPYRIGHT 2020 Public Library of Science</rights><rights>2020 Horita et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2020 Horita et al 2020 Horita et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-17e1abb53a0fd841be5ded08ea0dd6d927254d0c54376b8b47996df380aa727f3</citedby><cites>FETCH-LOGICAL-c692t-17e1abb53a0fd841be5ded08ea0dd6d927254d0c54376b8b47996df380aa727f3</cites><orcidid>0000-0002-1610-0175 ; 0000-0002-6728-5659</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7094855/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7094855/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23847,27903,27904,53769,53771,79346,79347</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32210454$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Du, Shao Jun</contributor><creatorcontrib>Horita, Tetsuya</creatorcontrib><creatorcontrib>Gaballah, Mohammed Hassan</creatorcontrib><creatorcontrib>Fukuta, Mamiko</creatorcontrib><creatorcontrib>Kanno, Sanae</creatorcontrib><creatorcontrib>Kato, Hideaki</creatorcontrib><creatorcontrib>Takamiya, Masataka</creatorcontrib><creatorcontrib>Aoki, Yasuhiro</creatorcontrib><title>Time course analysis of large-scale gene expression in incised muscle using correspondence analysis</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Studying the time course of gene expression in injured skeletal muscle would help to estimate the timing of injuries. In this study, we investigated large-scale gene expression in incision-injured mouse skeletal muscle by DNA microarray using correspondence analysis (CA). Biceps femoris muscle samples were collected 6, 12, and 24 hours after injury, and RNA was extracted and prepared for microarray analysis. On a 2-dimensional plot by CA, the genes (row score coordinate) located farther from each time series (column score coordinate) had more upregulation at particular times. Each gene was situated in 6 subdivided triangular areas according to the magnitude of the relationship of the fold change (FC) value at each time point compared to the control. In each area, genes for which the ratios of two particular FC values were close to 1 were distributed along the two border lines. There was a tendency for genes whose FC values were almost equal to be distributed near the intersection of these 6 areas. Therefore, the gene marker candidates for estimation of the timing of injuries were detectable according to the location on the CA plot. Moreover, gene sets created by a specific gene and its surrounding genes were composed of genes that showed similar or identical fluctuation patterns to the specific gene. In various analyses on these sets, significant gene ontology term and pathway activity may reflect changes in specific genes. In conclusion, analyses of gene sets based on CA plots is effective for investigation of the time-dependent fluctuation in gene expression after injury.</description><subject>Analysis</subject><subject>Biochemistry</subject><subject>Biology and Life Sciences</subject><subject>Cell cycle</subject><subject>Cytokines</subject><subject>Deoxyribonucleic acid</subject><subject>DNA</subject><subject>DNA chips</subject><subject>DNA microarrays</subject><subject>Flags</subject><subject>Forensic medicine</subject><subject>Forensic pathology</subject><subject>Gene expression</subject><subject>Genes</subject><subject>Genetic aspects</subject><subject>Genetic markers</subject><subject>Injuries</subject><subject>Injury analysis</subject><subject>Laboratory animals</subject><subject>Medicine and Health Sciences</subject><subject>Muscles</subject><subject>Musculoskeletal system</subject><subject>Ontology</subject><subject>Principal components analysis</subject><subject>Quality control</subject><subject>Research and Analysis Methods</subject><subject>Ribonucleic acid</subject><subject>RNA</subject><subject>Skeletal muscle</subject><subject>Skin</subject><subject>Time</subject><subject>Time dependence</subject><subject>Two dimensional analysis</subject><subject>University graduates</subject><subject>Values</subject><subject>Variance analysis</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><sourceid>DOA</sourceid><recordid>eNqNk99r1TAUgIsobk7_A9GCIPpwr_nZNC_CGFMvDAY6fQ1pctqbS9tck1a2_365u928lT1ICw3pd74kJ-dk2WuMlpgK_Gnjx9Drdrn1PSwRoUhQ8SQ7xpKSRUEQfXowPspexLhBiNOyKJ5nR5QQjBhnx5m5ch3kJrki5Dr5bqKLua_zVocGFtHoFvIGesjhehsgRuf73O1e4yLYvBujScQYXd8kTUhI2pCF3vzVvcye1bqN8Gr6nmQ_v5xfnX1bXFx-XZ2dXixMIcmwwAKwripONaptyXAF3IJFJWhkbWElEYQziwxnVBRVWTEhZWFrWiKtBRE1Pcne7r3b1kc15ScqQkuSSCxFIlZ7wnq9UdvgOh1ulNdO3U340CgdBpdOpKQh1IK0jNc1kzVoTQwGIxnWJeHaJtfnabWx6sAa6Ieg25l0_qd3a9X4P0ogyUrOk-DDJAj-9whxUJ2LBtpW9-DHu31TjgvOUULf_YM-frqJatKlKdfXPq1rdlJ1WuCSE4ZQkajlI1R6LHTOpGKqXZqfBXycBSRmgOuh0WOMavXj-_-zl7_m7PsDdg26HdbRt-OQSizOQbYHTfAxBqgfkoyR2vXCfTbUrhfU1Asp7M3hBT0E3Rc_vQWGEAW_</recordid><startdate>20200325</startdate><enddate>20200325</enddate><creator>Horita, Tetsuya</creator><creator>Gaballah, Mohammed Hassan</creator><creator>Fukuta, Mamiko</creator><creator>Kanno, Sanae</creator><creator>Kato, Hideaki</creator><creator>Takamiya, Masataka</creator><creator>Aoki, Yasuhiro</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-1610-0175</orcidid><orcidid>https://orcid.org/0000-0002-6728-5659</orcidid></search><sort><creationdate>20200325</creationdate><title>Time course analysis of large-scale gene expression in incised muscle using correspondence analysis</title><author>Horita, Tetsuya ; Gaballah, Mohammed Hassan ; Fukuta, Mamiko ; Kanno, Sanae ; Kato, Hideaki ; Takamiya, Masataka ; Aoki, Yasuhiro</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c692t-17e1abb53a0fd841be5ded08ea0dd6d927254d0c54376b8b47996df380aa727f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Analysis</topic><topic>Biochemistry</topic><topic>Biology and Life Sciences</topic><topic>Cell cycle</topic><topic>Cytokines</topic><topic>Deoxyribonucleic acid</topic><topic>DNA</topic><topic>DNA chips</topic><topic>DNA microarrays</topic><topic>Flags</topic><topic>Forensic medicine</topic><topic>Forensic pathology</topic><topic>Gene expression</topic><topic>Genes</topic><topic>Genetic aspects</topic><topic>Genetic markers</topic><topic>Injuries</topic><topic>Injury analysis</topic><topic>Laboratory animals</topic><topic>Medicine and Health Sciences</topic><topic>Muscles</topic><topic>Musculoskeletal system</topic><topic>Ontology</topic><topic>Principal components analysis</topic><topic>Quality control</topic><topic>Research and Analysis Methods</topic><topic>Ribonucleic acid</topic><topic>RNA</topic><topic>Skeletal muscle</topic><topic>Skin</topic><topic>Time</topic><topic>Time dependence</topic><topic>Two dimensional analysis</topic><topic>University graduates</topic><topic>Values</topic><topic>Variance analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Horita, Tetsuya</creatorcontrib><creatorcontrib>Gaballah, Mohammed Hassan</creatorcontrib><creatorcontrib>Fukuta, Mamiko</creatorcontrib><creatorcontrib>Kanno, Sanae</creatorcontrib><creatorcontrib>Kato, Hideaki</creatorcontrib><creatorcontrib>Takamiya, Masataka</creatorcontrib><creatorcontrib>Aoki, Yasuhiro</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Agriculture Science Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Nursing & Allied Health Premium</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Materials Science Collection</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Horita, Tetsuya</au><au>Gaballah, Mohammed Hassan</au><au>Fukuta, Mamiko</au><au>Kanno, Sanae</au><au>Kato, Hideaki</au><au>Takamiya, Masataka</au><au>Aoki, Yasuhiro</au><au>Du, Shao Jun</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Time course analysis of large-scale gene expression in incised muscle using correspondence analysis</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2020-03-25</date><risdate>2020</risdate><volume>15</volume><issue>3</issue><spage>e0230737</spage><epage>e0230737</epage><pages>e0230737-e0230737</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Studying the time course of gene expression in injured skeletal muscle would help to estimate the timing of injuries. In this study, we investigated large-scale gene expression in incision-injured mouse skeletal muscle by DNA microarray using correspondence analysis (CA). Biceps femoris muscle samples were collected 6, 12, and 24 hours after injury, and RNA was extracted and prepared for microarray analysis. On a 2-dimensional plot by CA, the genes (row score coordinate) located farther from each time series (column score coordinate) had more upregulation at particular times. Each gene was situated in 6 subdivided triangular areas according to the magnitude of the relationship of the fold change (FC) value at each time point compared to the control. In each area, genes for which the ratios of two particular FC values were close to 1 were distributed along the two border lines. There was a tendency for genes whose FC values were almost equal to be distributed near the intersection of these 6 areas. Therefore, the gene marker candidates for estimation of the timing of injuries were detectable according to the location on the CA plot. Moreover, gene sets created by a specific gene and its surrounding genes were composed of genes that showed similar or identical fluctuation patterns to the specific gene. In various analyses on these sets, significant gene ontology term and pathway activity may reflect changes in specific genes. In conclusion, analyses of gene sets based on CA plots is effective for investigation of the time-dependent fluctuation in gene expression after injury.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>32210454</pmid><doi>10.1371/journal.pone.0230737</doi><tpages>e0230737</tpages><orcidid>https://orcid.org/0000-0002-1610-0175</orcidid><orcidid>https://orcid.org/0000-0002-6728-5659</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2020-03, Vol.15 (3), p.e0230737-e0230737 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_2382996197 |
| source | PLoS; DOAJ Directory of Open Access Journals; PubMed Central; Free Full-Text Journals in Chemistry; EZB Electronic Journals Library |
| subjects | Analysis Biochemistry Biology and Life Sciences Cell cycle Cytokines Deoxyribonucleic acid DNA DNA chips DNA microarrays Flags Forensic medicine Forensic pathology Gene expression Genes Genetic aspects Genetic markers Injuries Injury analysis Laboratory animals Medicine and Health Sciences Muscles Musculoskeletal system Ontology Principal components analysis Quality control Research and Analysis Methods Ribonucleic acid RNA Skeletal muscle Skin Time Time dependence Two dimensional analysis University graduates Values Variance analysis |
| title | Time course analysis of large-scale gene expression in incised muscle using correspondence analysis |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-27T21%3A33%3A28IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Time%20course%20analysis%20of%20large-scale%20gene%20expression%20in%20incised%20muscle%20using%20correspondence%20analysis&rft.jtitle=PloS%20one&rft.au=Horita,%20Tetsuya&rft.date=2020-03-25&rft.volume=15&rft.issue=3&rft.spage=e0230737&rft.epage=e0230737&rft.pages=e0230737-e0230737&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0230737&rft_dat=%3Cgale_plos_%3EA618524006%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2382996197&rft_id=info:pmid/32210454&rft_galeid=A618524006&rft_doaj_id=oai_doaj_org_article_9c23de9d45ff49feaa2c1ec941a825ad&rfr_iscdi=true |