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Usual normalization strategies for gene expression studies impair the detection and analysis of circadian patterns
Recent studies have shown that transcriptomes from different tissues present circadian oscillations. Therefore, the endogenous variation of total RNA should be considered as a potential bias in circadian studies of gene expression. However, normalization strategies generally include the equalization...
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Published in: | Chronobiology international 2018-03, Vol.35 (3), p.378-391 |
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creator | Figueredo, Diego de Siqueira Barbosa, Mayara Rodrigues Coimbra, Daniel Gomes Dos Santos, José Luiz Araújo Costa, Ellyda Fernanda Lopes Koike, Bruna Del Vechio Alexandre Moreira, Magna Suzana de Andrade, Tiago Gomes |
description | Recent studies have shown that transcriptomes from different tissues present circadian oscillations. Therefore, the endogenous variation of total RNA should be considered as a potential bias in circadian studies of gene expression. However, normalization strategies generally include the equalization of total RNA concentration between samples prior to cDNA synthesis. Moreover, endogenous housekeeping genes (HKGs) frequently used for data normalization may exhibit circadian variation and distort experimental results if not detected or considered. In this study, we controlled experimental conditions from the amount of initial brain tissue samples through extraction steps, cDNA synthesis, and quantitative real time PCR (qPCR) to demonstrate a circadian oscillation of total RNA concentration. We also identified that the normalization of the RNA's yield affected the rhythmic profiles of different genes, including Per1-2 and Bmal1. Five widely used HKGs (Actb, Eif2a, Gapdh, Hprt1, and B2m) also presented rhythmic variations not detected by geNorm algorithm. In addition, the analysis of exogenous microRNAs (Cel-miR-54 and Cel-miR-39) spiked during RNA extraction suggests that the yield was affected by total RNA concentration, which may impact circadian studies of small RNAs. The results indicate that the approach of tissue normalization without total RNA equalization prior to cDNA synthesis can avoid bias from endogenous broad variations in transcript levels. Also, the circadian analysis of 2
data, without HKGs, may be an alternative for chronobiological studies under controlled experimental conditions. |
doi_str_mv | 10.1080/07420528.2017.1410168 |
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data, without HKGs, may be an alternative for chronobiological studies under controlled experimental conditions.</description><identifier>ISSN: 0742-0528</identifier><identifier>EISSN: 1525-6073</identifier><identifier>DOI: 10.1080/07420528.2017.1410168</identifier><identifier>PMID: 29219623</identifier><language>eng</language><publisher>England</publisher><subject>Algorithms ; Animals ; Brain - metabolism ; Circadian Rhythm ; DNA Primers ; Gene Expression Profiling - methods ; Gene Expression Regulation ; Genes, Essential ; Mice ; Mice, Inbred C57BL ; Real-Time Polymerase Chain Reaction ; RNA, Messenger - genetics ; Time Factors ; Transcriptome</subject><ispartof>Chronobiology international, 2018-03, Vol.35 (3), p.378-391</ispartof><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c356t-2bbf89308209f64e9025f40ded973271193bb6e6db1164744d325f893721ceef3</citedby><cites>FETCH-LOGICAL-c356t-2bbf89308209f64e9025f40ded973271193bb6e6db1164744d325f893721ceef3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29219623$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Figueredo, Diego de Siqueira</creatorcontrib><creatorcontrib>Barbosa, Mayara Rodrigues</creatorcontrib><creatorcontrib>Coimbra, Daniel Gomes</creatorcontrib><creatorcontrib>Dos Santos, José Luiz Araújo</creatorcontrib><creatorcontrib>Costa, Ellyda Fernanda Lopes</creatorcontrib><creatorcontrib>Koike, Bruna Del Vechio</creatorcontrib><creatorcontrib>Alexandre Moreira, Magna Suzana</creatorcontrib><creatorcontrib>de Andrade, Tiago Gomes</creatorcontrib><title>Usual normalization strategies for gene expression studies impair the detection and analysis of circadian patterns</title><title>Chronobiology international</title><addtitle>Chronobiol Int</addtitle><description>Recent studies have shown that transcriptomes from different tissues present circadian oscillations. Therefore, the endogenous variation of total RNA should be considered as a potential bias in circadian studies of gene expression. However, normalization strategies generally include the equalization of total RNA concentration between samples prior to cDNA synthesis. Moreover, endogenous housekeeping genes (HKGs) frequently used for data normalization may exhibit circadian variation and distort experimental results if not detected or considered. In this study, we controlled experimental conditions from the amount of initial brain tissue samples through extraction steps, cDNA synthesis, and quantitative real time PCR (qPCR) to demonstrate a circadian oscillation of total RNA concentration. We also identified that the normalization of the RNA's yield affected the rhythmic profiles of different genes, including Per1-2 and Bmal1. Five widely used HKGs (Actb, Eif2a, Gapdh, Hprt1, and B2m) also presented rhythmic variations not detected by geNorm algorithm. In addition, the analysis of exogenous microRNAs (Cel-miR-54 and Cel-miR-39) spiked during RNA extraction suggests that the yield was affected by total RNA concentration, which may impact circadian studies of small RNAs. The results indicate that the approach of tissue normalization without total RNA equalization prior to cDNA synthesis can avoid bias from endogenous broad variations in transcript levels. Also, the circadian analysis of 2
data, without HKGs, may be an alternative for chronobiological studies under controlled experimental conditions.</description><subject>Algorithms</subject><subject>Animals</subject><subject>Brain - metabolism</subject><subject>Circadian Rhythm</subject><subject>DNA Primers</subject><subject>Gene Expression Profiling - methods</subject><subject>Gene Expression Regulation</subject><subject>Genes, Essential</subject><subject>Mice</subject><subject>Mice, Inbred C57BL</subject><subject>Real-Time Polymerase Chain Reaction</subject><subject>RNA, Messenger - genetics</subject><subject>Time Factors</subject><subject>Transcriptome</subject><issn>0742-0528</issn><issn>1525-6073</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNo9kMtKxDAUQIMozjj6CUqWbjrm0SbNUsQXDLhx1iFtbsZIXyYpqF9v64wuLlncc3LhIHRJyZqSktwQmTNSsHLNCJVrmlNCRXmElrRgRSaI5MdoOTPZDC3QWYzvhEyi4KdowRSjSjC-RGEbR9Pgrg-tafy3Sb7vcEzBJNh5iNj1Ae-gAwyfQ4AY9-vRzjvfDsYHnN4AW0hQ_7qms9OY5iv6iHuHax9qY73p8GBSgtDFc3TiTBPh4vCu0Pbh_vXuKdu8PD7f3W6ymhciZayqXKk4KRlRTuSgCCtcTixYJTmTlCpeVQKErSgVucxzyydgMiSjNYDjK3S9_3cI_ccIMenWxxqaxnTQj1FTJQvCmOR0Qos9Woc-xgBOD8G3JnxpSvScW__l1nNufcg9eVeHE2PVgv23_vryHx6-fFY</recordid><startdate>20180304</startdate><enddate>20180304</enddate><creator>Figueredo, Diego de Siqueira</creator><creator>Barbosa, Mayara Rodrigues</creator><creator>Coimbra, Daniel Gomes</creator><creator>Dos Santos, José Luiz Araújo</creator><creator>Costa, Ellyda Fernanda Lopes</creator><creator>Koike, Bruna Del Vechio</creator><creator>Alexandre Moreira, Magna Suzana</creator><creator>de Andrade, Tiago Gomes</creator><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20180304</creationdate><title>Usual normalization strategies for gene expression studies impair the detection and analysis of circadian patterns</title><author>Figueredo, Diego de Siqueira ; Barbosa, Mayara Rodrigues ; Coimbra, Daniel Gomes ; Dos Santos, José Luiz Araújo ; Costa, Ellyda Fernanda Lopes ; Koike, Bruna Del Vechio ; Alexandre Moreira, Magna Suzana ; de Andrade, Tiago Gomes</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c356t-2bbf89308209f64e9025f40ded973271193bb6e6db1164744d325f893721ceef3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Algorithms</topic><topic>Animals</topic><topic>Brain - metabolism</topic><topic>Circadian Rhythm</topic><topic>DNA Primers</topic><topic>Gene Expression Profiling - methods</topic><topic>Gene Expression Regulation</topic><topic>Genes, Essential</topic><topic>Mice</topic><topic>Mice, Inbred C57BL</topic><topic>Real-Time Polymerase Chain Reaction</topic><topic>RNA, Messenger - genetics</topic><topic>Time Factors</topic><topic>Transcriptome</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Figueredo, Diego de Siqueira</creatorcontrib><creatorcontrib>Barbosa, Mayara Rodrigues</creatorcontrib><creatorcontrib>Coimbra, Daniel Gomes</creatorcontrib><creatorcontrib>Dos Santos, José Luiz Araújo</creatorcontrib><creatorcontrib>Costa, Ellyda Fernanda Lopes</creatorcontrib><creatorcontrib>Koike, Bruna Del Vechio</creatorcontrib><creatorcontrib>Alexandre Moreira, Magna Suzana</creatorcontrib><creatorcontrib>de Andrade, Tiago Gomes</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Chronobiology international</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Figueredo, Diego de Siqueira</au><au>Barbosa, Mayara Rodrigues</au><au>Coimbra, Daniel Gomes</au><au>Dos Santos, José Luiz Araújo</au><au>Costa, Ellyda Fernanda Lopes</au><au>Koike, Bruna Del Vechio</au><au>Alexandre Moreira, Magna Suzana</au><au>de Andrade, Tiago Gomes</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Usual normalization strategies for gene expression studies impair the detection and analysis of circadian patterns</atitle><jtitle>Chronobiology international</jtitle><addtitle>Chronobiol Int</addtitle><date>2018-03-04</date><risdate>2018</risdate><volume>35</volume><issue>3</issue><spage>378</spage><epage>391</epage><pages>378-391</pages><issn>0742-0528</issn><eissn>1525-6073</eissn><abstract>Recent studies have shown that transcriptomes from different tissues present circadian oscillations. Therefore, the endogenous variation of total RNA should be considered as a potential bias in circadian studies of gene expression. However, normalization strategies generally include the equalization of total RNA concentration between samples prior to cDNA synthesis. Moreover, endogenous housekeeping genes (HKGs) frequently used for data normalization may exhibit circadian variation and distort experimental results if not detected or considered. In this study, we controlled experimental conditions from the amount of initial brain tissue samples through extraction steps, cDNA synthesis, and quantitative real time PCR (qPCR) to demonstrate a circadian oscillation of total RNA concentration. We also identified that the normalization of the RNA's yield affected the rhythmic profiles of different genes, including Per1-2 and Bmal1. Five widely used HKGs (Actb, Eif2a, Gapdh, Hprt1, and B2m) also presented rhythmic variations not detected by geNorm algorithm. 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data, without HKGs, may be an alternative for chronobiological studies under controlled experimental conditions.</abstract><cop>England</cop><pmid>29219623</pmid><doi>10.1080/07420528.2017.1410168</doi><tpages>14</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Animals Brain - metabolism Circadian Rhythm DNA Primers Gene Expression Profiling - methods Gene Expression Regulation Genes, Essential Mice Mice, Inbred C57BL Real-Time Polymerase Chain Reaction RNA, Messenger - genetics Time Factors Transcriptome |
title | Usual normalization strategies for gene expression studies impair the detection and analysis of circadian patterns |
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