Untangling the transcriptome from fungus-infected plant tissues.
Identifieur interne : 002430 ( Main/Exploration ); précédent : 002429; suivant : 002431Untangling the transcriptome from fungus-infected plant tissues.
Auteurs : Sheng Zhu [République populaire de Chine] ; Yong-Mei Dai ; Xin-Ye Zhang ; Jian-Ren Ye ; Ming-Xiu Wang ; Min-Ren HuangSource :
- Gene [ 1879-0038 ] ; 2013.
Descripteurs français
- KwdFr :
- Analyse de profil d'expression de gènes (méthodes), Analyse de séquence d'ARN (MeSH), Ascomycota (génétique), Ascomycota (pathogénicité), Banque de gènes (MeSH), Feuilles de plante (génétique), Feuilles de plante (microbiologie), Interactions hôte-pathogène (MeSH), Maladies des plantes (microbiologie), Protéines végétales (génétique), Protéines végétales (métabolisme), Régulation de l'expression des gènes végétaux (MeSH), Étiquettes de séquences exprimées (MeSH).
- MESH :
- génétique : Ascomycota, Feuilles de plante, Protéines végétales.
- microbiologie : Feuilles de plante, Maladies des plantes.
- métabolisme : Protéines végétales.
- méthodes : Analyse de profil d'expression de gènes.
- pathogénicité : Ascomycota.
- Analyse de séquence d'ARN, Banque de gènes, Interactions hôte-pathogène, Régulation de l'expression des gènes végétaux, Étiquettes de séquences exprimées.
English descriptors
- KwdEn :
- Ascomycota (genetics), Ascomycota (pathogenicity), Expressed Sequence Tags (MeSH), Gene Expression Profiling (methods), Gene Expression Regulation, Plant (MeSH), Gene Library (MeSH), Host-Pathogen Interactions (MeSH), Plant Diseases (microbiology), Plant Leaves (genetics), Plant Leaves (microbiology), Plant Proteins (genetics), Plant Proteins (metabolism), Sequence Analysis, RNA (MeSH).
- MESH :
- chemical , genetics : Plant Proteins.
- genetics : Ascomycota, Plant Leaves.
- chemical , metabolism : Plant Proteins.
- methods : Gene Expression Profiling.
- microbiology : Plant Diseases, Plant Leaves.
- pathogenicity : Ascomycota.
- Expressed Sequence Tags, Gene Expression Regulation, Plant, Gene Library, Host-Pathogen Interactions, Sequence Analysis, RNA.
Abstract
The development of sequencing technology allows low-cost generation of sequence data. The huge amount of raw sequence data now available has introduced many challenges associated with analysis of these large-scale data banks. For example, it is very important to distinguish materials of plant and fungal origin in fungus-infected plant tissue. The origin of transcripts that were sequenced from Library 895-M6 (poplar tissue infected by Marssonina brunnea) on Illumina/Solexa GA IIx was determined by combining three methods: (1) based on the taxonomic information of homologous sequences; (2) based on the reference genome sequence; (3) based on the transcriptome sequence of the host and its pathogen obtained from Library 895 (poplar) and Library M6 (M. brunnea) as well as Library 895-M6 (mixture of poplar and M. brunnea). We idenified accurately the origin of 80,978 (99.5%) contigs in the mixed poplar and M. brunnea sample (Library 895-M6) by integrating the results from the three methods. The results of this study demonstrate that a combination of these three approaches described here is an effective strategy for determining the origin of sequences in a mixed pool, and provides a basis for further transcriptome analysis of the mixed sample.
DOI: 10.1016/j.gene.2013.02.023
PubMed: 23466979
Affiliations:
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Zhang</name></author><author><name sortKey="Ye, Jian Ren" sort="Ye, Jian Ren" uniqKey="Ye J" first="Jian-Ren" last="Ye">Jian-Ren Ye</name></author><author><name sortKey="Wang, Ming Xiu" sort="Wang, Ming Xiu" uniqKey="Wang M" first="Ming-Xiu" last="Wang">Ming-Xiu Wang</name></author><author><name sortKey="Huang, Min Ren" sort="Huang, Min Ren" uniqKey="Huang M" first="Min-Ren" last="Huang">Min-Ren Huang</name></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2013">2013</date><idno type="RBID">pubmed:23466979</idno><idno type="pmid">23466979</idno><idno type="doi">10.1016/j.gene.2013.02.023</idno><idno type="wicri:Area/Main/Corpus">002676</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">002676</idno><idno type="wicri:Area/Main/Curation">002676</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Curation">002676</idno><idno 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first="Xin-Ye" last="Zhang">Xin-Ye Zhang</name></author><author><name sortKey="Ye, Jian Ren" sort="Ye, Jian Ren" uniqKey="Ye J" first="Jian-Ren" last="Ye">Jian-Ren Ye</name></author><author><name sortKey="Wang, Ming Xiu" sort="Wang, Ming Xiu" uniqKey="Wang M" first="Ming-Xiu" last="Wang">Ming-Xiu Wang</name></author><author><name sortKey="Huang, Min Ren" sort="Huang, Min Ren" uniqKey="Huang M" first="Min-Ren" last="Huang">Min-Ren Huang</name></author></analytic><series><title level="j">Gene</title><idno type="eISSN">1879-0038</idno><imprint><date when="2013" type="published">2013</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Ascomycota (genetics)</term><term>Ascomycota (pathogenicity)</term><term>Expressed Sequence Tags (MeSH)</term><term>Gene Expression Profiling (methods)</term><term>Gene Expression Regulation, Plant (MeSH)</term><term>Gene Library (MeSH)</term><term>Host-Pathogen Interactions (MeSH)</term><term>Plant Diseases (microbiology)</term><term>Plant Leaves (genetics)</term><term>Plant Leaves (microbiology)</term><term>Plant Proteins (genetics)</term><term>Plant Proteins (metabolism)</term><term>Sequence Analysis, RNA (MeSH)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Analyse de profil d'expression de gènes (méthodes)</term><term>Analyse de séquence d'ARN (MeSH)</term><term>Ascomycota (génétique)</term><term>Ascomycota (pathogénicité)</term><term>Banque de gènes (MeSH)</term><term>Feuilles de plante (génétique)</term><term>Feuilles de plante (microbiologie)</term><term>Interactions hôte-pathogène (MeSH)</term><term>Maladies des plantes (microbiologie)</term><term>Protéines végétales (génétique)</term><term>Protéines végétales (métabolisme)</term><term>Régulation de l'expression des gènes végétaux (MeSH)</term><term>Étiquettes de séquences exprimées (MeSH)</term></keywords><keywords scheme="MESH" type="chemical" qualifier="genetics" 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The huge amount of raw sequence data now available has introduced many challenges associated with analysis of these large-scale data banks. For example, it is very important to distinguish materials of plant and fungal origin in fungus-infected plant tissue. The origin of transcripts that were sequenced from Library 895-M6 (poplar tissue infected by Marssonina brunnea) on Illumina/Solexa GA IIx was determined by combining three methods: (1) based on the taxonomic information of homologous sequences; (2) based on the reference genome sequence; (3) based on the transcriptome sequence of the host and its pathogen obtained from Library 895 (poplar) and Library M6 (M. brunnea) as well as Library 895-M6 (mixture of poplar and M. brunnea). We idenified accurately the origin of 80,978 (99.5%) contigs in the mixed poplar and M. brunnea sample (Library 895-M6) by integrating the results from the three methods. The results of this study demonstrate that a combination of these three approaches described here is an effective strategy for determining the origin of sequences in a mixed pool, and provides a basis for further transcriptome analysis of the mixed sample.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">23466979</PMID><DateCompleted><Year>2013</Year><Month>05</Month><Day>20</Day></DateCompleted><DateRevised><Year>2013</Year><Month>04</Month><Day>01</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1879-0038</ISSN><JournalIssue CitedMedium="Internet"><Volume>519</Volume><Issue>2</Issue><PubDate><Year>2013</Year><Month>May</Month><Day>01</Day></PubDate></JournalIssue><Title>Gene</Title><ISOAbbreviation>Gene</ISOAbbreviation></Journal><ArticleTitle>Untangling the transcriptome from fungus-infected plant tissues.</ArticleTitle><Pagination><MedlinePgn>238-44</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1016/j.gene.2013.02.023</ELocationID><ELocationID EIdType="pii" ValidYN="Y">S0378-1119(13)00200-X</ELocationID><Abstract><AbstractText>The development of sequencing technology allows low-cost generation of sequence data. The huge amount of raw sequence data now available has introduced many challenges associated with analysis of these large-scale data banks. For example, it is very important to distinguish materials of plant and fungal origin in fungus-infected plant tissue. The origin of transcripts that were sequenced from Library 895-M6 (poplar tissue infected by Marssonina brunnea) on Illumina/Solexa GA IIx was determined by combining three methods: (1) based on the taxonomic information of homologous sequences; (2) based on the reference genome sequence; (3) based on the transcriptome sequence of the host and its pathogen obtained from Library 895 (poplar) and Library M6 (M. brunnea) as well as Library 895-M6 (mixture of poplar and M. brunnea). We idenified accurately the origin of 80,978 (99.5%) contigs in the mixed poplar and M. brunnea sample (Library 895-M6) by integrating the results from the three methods. The results of this study demonstrate that a combination of these three approaches described here is an effective strategy for determining the origin of sequences in a mixed pool, and provides a basis for further transcriptome analysis of the mixed sample.</AbstractText><CopyrightInformation>Crown Copyright © 2013. Published by Elsevier B.V. All rights reserved.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Zhu</LastName><ForeName>Sheng</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>Jiangsu Key Laboratory for Poplar Germplasm Enhancement and Variety Improvement, Nanjing Forestry University, Nanjing 210037, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Dai</LastName><ForeName>Yong-Mei</ForeName><Initials>YM</Initials></Author><Author ValidYN="Y"><LastName>Zhang</LastName><ForeName>Xin-Ye</ForeName><Initials>XY</Initials></Author><Author ValidYN="Y"><LastName>Ye</LastName><ForeName>Jian-Ren</ForeName><Initials>JR</Initials></Author><Author ValidYN="Y"><LastName>Wang</LastName><ForeName>Ming-Xiu</ForeName><Initials>MX</Initials></Author><Author ValidYN="Y"><LastName>Huang</LastName><ForeName>Min-Ren</ForeName><Initials>MR</Initials></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal 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PubStatus="medline"><Year>2013</Year><Month>5</Month><Day>22</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">23466979</ArticleId><ArticleId IdType="pii">S0378-1119(13)00200-X</ArticleId><ArticleId IdType="doi">10.1016/j.gene.2013.02.023</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>République populaire de Chine</li></country></list><tree><noCountry><name sortKey="Dai, Yong Mei" sort="Dai, Yong Mei" uniqKey="Dai Y" first="Yong-Mei" last="Dai">Yong-Mei Dai</name><name sortKey="Huang, Min Ren" sort="Huang, Min Ren" uniqKey="Huang M" first="Min-Ren" last="Huang">Min-Ren Huang</name><name sortKey="Wang, Ming Xiu" sort="Wang, Ming Xiu" uniqKey="Wang M" first="Ming-Xiu" last="Wang">Ming-Xiu Wang</name><name sortKey="Ye, Jian Ren" sort="Ye, Jian Ren" uniqKey="Ye J" first="Jian-Ren" last="Ye">Jian-Ren Ye</name><name sortKey="Zhang, Xin Ye" sort="Zhang, Xin Ye" uniqKey="Zhang X" first="Xin-Ye" last="Zhang">Xin-Ye Zhang</name></noCountry><country name="République populaire de Chine"><noRegion><name sortKey="Zhu, Sheng" sort="Zhu, Sheng" uniqKey="Zhu S" first="Sheng" last="Zhu">Sheng Zhu</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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