Detection of QTLs with additive effects and additive-by-environment interaction effects on panicle number in rice (Oryza sativa L.) with single-segment substitution lines
A novel population consisting of 35 single-segment substitution lines (SSSLs) originating from crosses between the recipient parent, Hua-jing-xian 74 (HJX74), and 17 donor parents was evaluated in six cropping season environments to reveal the genetic basis of genetic main effect (G) and genotype-by...
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| creator | Liu, Guifu Zhang, Zemin Zhu, Haitao Zhao, Fangming Ding, Xiaohua Zeng, Ruizhen Li, Wentao Zhang, Guiquan |
| description | A novel population consisting of 35 single-segment substitution lines (SSSLs) originating from crosses between the recipient parent, Hua-jing-xian 74 (HJX74), and 17 donor parents was evaluated in six cropping season environments to reveal the genetic basis of genetic main effect (G) and genotype-by-environment interaction effect (GE) for panicle number (PN) in rice. Subsets of lines were grown in up to six environments. An indirect analysis method was applied, in which the total genetic effect was first partitioned into G and GE by using the mixed linear-model approach, and then QTL (quantitative trait locus) analyses on these effects were conducted separately. At least 18 QTLs for PN in rice were detected and identified on 9 of 12 rice chromosomes. A single QTL effect (a + ae) ranging from -1.5 to 1.2 was divided into two components, additive effect (a) and additive x environment interaction effect (ae). A total number of 9 and 16 QTLs were identified with a ranging from -0.4 to 0.6 and ae ranging from -1.0 to 0.6, respectively, the former being stable but the latter unstable across environments. Three types of QTLs were suggested according to their effects expressed. Two QTLs (Pn-1b and Pn-6d) expressed stably across environments due to the association with only a, nine QTLs (Pn-1a, Pn-3c, Pn-3d, Pn-4, Pn-6a, Pn-6b, Pn-8, Pn-9 and Pn-12) with only ae were unstable, and the remaining seven of QTLs were identified with both a and ae, which also were unstable across environments. This is the first report on the detection of QE (QTL-by-environment interaction effect) of QTLs with SSSLs. Our results illustrate the efficiency of characterizing QTLs and analyzing action of QTLs through SSSLs, and further demonstrate that QE is an important property of many QTLs. Information provided in this paper could be used in the application of marker-assisted selection to manipulate PN in rice. |
| doi_str_mv | 10.1007/s00122-008-0724-4 |
| format | Article |
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Subsets of lines were grown in up to six environments. An indirect analysis method was applied, in which the total genetic effect was first partitioned into G and GE by using the mixed linear-model approach, and then QTL (quantitative trait locus) analyses on these effects were conducted separately. At least 18 QTLs for PN in rice were detected and identified on 9 of 12 rice chromosomes. A single QTL effect (a + ae) ranging from -1.5 to 1.2 was divided into two components, additive effect (a) and additive x environment interaction effect (ae). A total number of 9 and 16 QTLs were identified with a ranging from -0.4 to 0.6 and ae ranging from -1.0 to 0.6, respectively, the former being stable but the latter unstable across environments. Three types of QTLs were suggested according to their effects expressed. Two QTLs (Pn-1b and Pn-6d) expressed stably across environments due to the association with only a, nine QTLs (Pn-1a, Pn-3c, Pn-3d, Pn-4, Pn-6a, Pn-6b, Pn-8, Pn-9 and Pn-12) with only ae were unstable, and the remaining seven of QTLs were identified with both a and ae, which also were unstable across environments. This is the first report on the detection of QE (QTL-by-environment interaction effect) of QTLs with SSSLs. Our results illustrate the efficiency of characterizing QTLs and analyzing action of QTLs through SSSLs, and further demonstrate that QE is an important property of many QTLs. Information provided in this paper could be used in the application of marker-assisted selection to manipulate PN in rice.</description><identifier>ISSN: 0040-5752</identifier><identifier>EISSN: 1432-2242</identifier><identifier>DOI: 10.1007/s00122-008-0724-4</identifier><identifier>PMID: 18274724</identifier><identifier>CODEN: THAGA6</identifier><language>eng</language><publisher>Berlin/Heidelberg: Berlin/Heidelberg : Springer-Verlag</publisher><subject>Agriculture ; Biochemistry ; Biological and medical sciences ; Biology ; Biomedical and Life Sciences ; Biotechnology ; Cereals ; Chromosome Mapping ; Chromosomes, Plant - genetics ; Classical genetics, quantitative genetics, hybrids ; Environment ; Fundamental and applied biological sciences. Psychology ; Genetics of eukaryotes. Biological and molecular evolution ; Genomes ; Life Sciences ; Original Paper ; Oryza - genetics ; Oryza - growth & development ; Oryza sativa ; Phenotype ; Plant Biochemistry ; Plant Breeding/Biotechnology ; Plant Genetics and Genomics ; Pteridophyta, spermatophyta ; Quantitative Trait Loci ; Rice ; Vegetals</subject><ispartof>Theoretical and applied genetics, 2008-05, Vol.116 (7), p.923-931</ispartof><rights>Springer-Verlag 2008</rights><rights>2008 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c454t-5d30e243e2669b76557163caea1d9a68bce4afe0e66719d5094773a4812902fd3</citedby><cites>FETCH-LOGICAL-c454t-5d30e243e2669b76557163caea1d9a68bce4afe0e66719d5094773a4812902fd3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00122-008-0724-4$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00122-008-0724-4$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=20291622$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/18274724$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Liu, Guifu</creatorcontrib><creatorcontrib>Zhang, Zemin</creatorcontrib><creatorcontrib>Zhu, Haitao</creatorcontrib><creatorcontrib>Zhao, Fangming</creatorcontrib><creatorcontrib>Ding, Xiaohua</creatorcontrib><creatorcontrib>Zeng, Ruizhen</creatorcontrib><creatorcontrib>Li, Wentao</creatorcontrib><creatorcontrib>Zhang, Guiquan</creatorcontrib><title>Detection of QTLs with additive effects and additive-by-environment interaction effects on panicle number in rice (Oryza sativa L.) with single-segment substitution lines</title><title>Theoretical and applied genetics</title><addtitle>Theor Appl Genet</addtitle><addtitle>Theor Appl Genet</addtitle><description>A novel population consisting of 35 single-segment substitution lines (SSSLs) originating from crosses between the recipient parent, Hua-jing-xian 74 (HJX74), and 17 donor parents was evaluated in six cropping season environments to reveal the genetic basis of genetic main effect (G) and genotype-by-environment interaction effect (GE) for panicle number (PN) in rice. Subsets of lines were grown in up to six environments. An indirect analysis method was applied, in which the total genetic effect was first partitioned into G and GE by using the mixed linear-model approach, and then QTL (quantitative trait locus) analyses on these effects were conducted separately. At least 18 QTLs for PN in rice were detected and identified on 9 of 12 rice chromosomes. A single QTL effect (a + ae) ranging from -1.5 to 1.2 was divided into two components, additive effect (a) and additive x environment interaction effect (ae). A total number of 9 and 16 QTLs were identified with a ranging from -0.4 to 0.6 and ae ranging from -1.0 to 0.6, respectively, the former being stable but the latter unstable across environments. Three types of QTLs were suggested according to their effects expressed. Two QTLs (Pn-1b and Pn-6d) expressed stably across environments due to the association with only a, nine QTLs (Pn-1a, Pn-3c, Pn-3d, Pn-4, Pn-6a, Pn-6b, Pn-8, Pn-9 and Pn-12) with only ae were unstable, and the remaining seven of QTLs were identified with both a and ae, which also were unstable across environments. This is the first report on the detection of QE (QTL-by-environment interaction effect) of QTLs with SSSLs. Our results illustrate the efficiency of characterizing QTLs and analyzing action of QTLs through SSSLs, and further demonstrate that QE is an important property of many QTLs. Information provided in this paper could be used in the application of marker-assisted selection to manipulate PN in rice.</description><subject>Agriculture</subject><subject>Biochemistry</subject><subject>Biological and medical sciences</subject><subject>Biology</subject><subject>Biomedical and Life Sciences</subject><subject>Biotechnology</subject><subject>Cereals</subject><subject>Chromosome Mapping</subject><subject>Chromosomes, Plant - genetics</subject><subject>Classical genetics, quantitative genetics, hybrids</subject><subject>Environment</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Genetics of eukaryotes. Biological and molecular evolution</subject><subject>Genomes</subject><subject>Life Sciences</subject><subject>Original Paper</subject><subject>Oryza - genetics</subject><subject>Oryza - growth & development</subject><subject>Oryza sativa</subject><subject>Phenotype</subject><subject>Plant Biochemistry</subject><subject>Plant Breeding/Biotechnology</subject><subject>Plant Genetics and Genomics</subject><subject>Pteridophyta, spermatophyta</subject><subject>Quantitative Trait Loci</subject><subject>Rice</subject><subject>Vegetals</subject><issn>0040-5752</issn><issn>1432-2242</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2008</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNqFkU1v1DAQhiMEokvhB3ABCwkEB5fxxB_JEZVPaaUK0Z4jJ5ksrhJnaydFy0_iV-JtllbiACdbnmee8ejNsqcCTgSAeRsBBCIHKDgYlFzey1ZC5sgRJd7PVgASuDIKj7JHMV4CACrIH2ZHokAjU8cq-_WeJmomN3o2duzr-TqyH276zmzbusldE6OuS_XIrG9vH3m94-SvXRj9QH5izk8U7GL5w6fr1nrX9MT8PNQUEsWCa4i9Pgu7n5ZFm1SWrU_eLBOj85ueeKTNjTPOdZzcNN9Ie-cpPs4edLaP9ORwHmcXHz-cn37m67NPX07frXkjlZy4anMglDmh1mVttFJG6LyxZEVbWl3UDUnbEZDWRpStglIak1tZCCwBuzY_zl4t3m0Yr2aKUzW42FDfW0_jHCsDsjRSqf-CCDqhSibwxV_g5TgHn5ZIjEwBaRAJEgvUhDHGQF21DW6wYVcJqPZxV0vcVYq72sdd7cXPDuK5Hqi96zjkm4CXB8DGxvZdsL5x8ZZDwFJoxMThwsVU8hsKdz_81_TnS1Nnx8puQhJffMO0SmIKk5eY_wbdE8y1</recordid><startdate>20080501</startdate><enddate>20080501</enddate><creator>Liu, Guifu</creator><creator>Zhang, Zemin</creator><creator>Zhu, Haitao</creator><creator>Zhao, Fangming</creator><creator>Ding, Xiaohua</creator><creator>Zeng, Ruizhen</creator><creator>Li, Wentao</creator><creator>Zhang, Guiquan</creator><general>Berlin/Heidelberg : Springer-Verlag</general><general>Springer-Verlag</general><general>Springer</general><general>Springer Nature B.V</general><scope>FBQ</scope><scope>IQODW</scope><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>3V.</scope><scope>7SS</scope><scope>7TK</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88E</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>RC3</scope><scope>7X8</scope></search><sort><creationdate>20080501</creationdate><title>Detection of QTLs with additive effects and additive-by-environment interaction effects on panicle number in rice (Oryza sativa L.) with single-segment substitution lines</title><author>Liu, Guifu ; Zhang, Zemin ; Zhu, Haitao ; Zhao, Fangming ; Ding, Xiaohua ; Zeng, Ruizhen ; Li, Wentao ; Zhang, Guiquan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c454t-5d30e243e2669b76557163caea1d9a68bce4afe0e66719d5094773a4812902fd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2008</creationdate><topic>Agriculture</topic><topic>Biochemistry</topic><topic>Biological and medical sciences</topic><topic>Biology</topic><topic>Biomedical and Life Sciences</topic><topic>Biotechnology</topic><topic>Cereals</topic><topic>Chromosome Mapping</topic><topic>Chromosomes, Plant - genetics</topic><topic>Classical genetics, quantitative genetics, hybrids</topic><topic>Environment</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>Genetics of eukaryotes. Biological and molecular evolution</topic><topic>Genomes</topic><topic>Life Sciences</topic><topic>Original Paper</topic><topic>Oryza - genetics</topic><topic>Oryza - growth & development</topic><topic>Oryza sativa</topic><topic>Phenotype</topic><topic>Plant Biochemistry</topic><topic>Plant Breeding/Biotechnology</topic><topic>Plant Genetics and Genomics</topic><topic>Pteridophyta, spermatophyta</topic><topic>Quantitative Trait Loci</topic><topic>Rice</topic><topic>Vegetals</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Guifu</creatorcontrib><creatorcontrib>Zhang, Zemin</creatorcontrib><creatorcontrib>Zhu, Haitao</creatorcontrib><creatorcontrib>Zhao, Fangming</creatorcontrib><creatorcontrib>Ding, Xiaohua</creatorcontrib><creatorcontrib>Zeng, Ruizhen</creatorcontrib><creatorcontrib>Li, Wentao</creatorcontrib><creatorcontrib>Zhang, Guiquan</creatorcontrib><collection>AGRIS</collection><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Neurosciences Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Biology Database (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech 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>ProQuest Central (Alumni)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</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>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Biological Sciences</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Biological Science Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Theoretical and applied genetics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liu, Guifu</au><au>Zhang, Zemin</au><au>Zhu, Haitao</au><au>Zhao, Fangming</au><au>Ding, Xiaohua</au><au>Zeng, Ruizhen</au><au>Li, Wentao</au><au>Zhang, Guiquan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Detection of QTLs with additive effects and additive-by-environment interaction effects on panicle number in rice (Oryza sativa L.) with single-segment substitution lines</atitle><jtitle>Theoretical and applied genetics</jtitle><stitle>Theor Appl Genet</stitle><addtitle>Theor Appl Genet</addtitle><date>2008-05-01</date><risdate>2008</risdate><volume>116</volume><issue>7</issue><spage>923</spage><epage>931</epage><pages>923-931</pages><issn>0040-5752</issn><eissn>1432-2242</eissn><coden>THAGA6</coden><abstract>A novel population consisting of 35 single-segment substitution lines (SSSLs) originating from crosses between the recipient parent, Hua-jing-xian 74 (HJX74), and 17 donor parents was evaluated in six cropping season environments to reveal the genetic basis of genetic main effect (G) and genotype-by-environment interaction effect (GE) for panicle number (PN) in rice. Subsets of lines were grown in up to six environments. An indirect analysis method was applied, in which the total genetic effect was first partitioned into G and GE by using the mixed linear-model approach, and then QTL (quantitative trait locus) analyses on these effects were conducted separately. At least 18 QTLs for PN in rice were detected and identified on 9 of 12 rice chromosomes. A single QTL effect (a + ae) ranging from -1.5 to 1.2 was divided into two components, additive effect (a) and additive x environment interaction effect (ae). A total number of 9 and 16 QTLs were identified with a ranging from -0.4 to 0.6 and ae ranging from -1.0 to 0.6, respectively, the former being stable but the latter unstable across environments. Three types of QTLs were suggested according to their effects expressed. Two QTLs (Pn-1b and Pn-6d) expressed stably across environments due to the association with only a, nine QTLs (Pn-1a, Pn-3c, Pn-3d, Pn-4, Pn-6a, Pn-6b, Pn-8, Pn-9 and Pn-12) with only ae were unstable, and the remaining seven of QTLs were identified with both a and ae, which also were unstable across environments. This is the first report on the detection of QE (QTL-by-environment interaction effect) of QTLs with SSSLs. Our results illustrate the efficiency of characterizing QTLs and analyzing action of QTLs through SSSLs, and further demonstrate that QE is an important property of many QTLs. Information provided in this paper could be used in the application of marker-assisted selection to manipulate PN in rice.</abstract><cop>Berlin/Heidelberg</cop><pub>Berlin/Heidelberg : Springer-Verlag</pub><pmid>18274724</pmid><doi>10.1007/s00122-008-0724-4</doi><tpages>9</tpages></addata></record> |
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| subjects | Agriculture Biochemistry Biological and medical sciences Biology Biomedical and Life Sciences Biotechnology Cereals Chromosome Mapping Chromosomes, Plant - genetics Classical genetics, quantitative genetics, hybrids Environment Fundamental and applied biological sciences. Psychology Genetics of eukaryotes. Biological and molecular evolution Genomes Life Sciences Original Paper Oryza - genetics Oryza - growth & development Oryza sativa Phenotype Plant Biochemistry Plant Breeding/Biotechnology Plant Genetics and Genomics Pteridophyta, spermatophyta Quantitative Trait Loci Rice Vegetals |
| title | Detection of QTLs with additive effects and additive-by-environment interaction effects on panicle number in rice (Oryza sativa L.) with single-segment substitution lines |
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