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QTL Mapping in Three Rice Populations Uncovers Major Genomic Regions Associated with African Rice Gall Midge Resistance
African rice gall midge (AfRGM) is one of the most destructive pests of irrigated and lowland African ecologies. This study aimed to identify the quantitative trait loci (QTL) associated with AfRGM pest incidence and resistance in three independent bi-parental rice populations (ITA306xBW348-1, ITA30...
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Published in: | PloS one 2016-08, Vol.11 (8), p.e0160749-e0160749 |
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creator | Yao, Nasser Lee, Cheng-Ruei Semagn, Kassa Sow, Mounirou Nwilene, Francis Kolade, Olufisayo Bocco, Roland Oyetunji, Olumoye Mitchell-Olds, Thomas Ndjiondjop, Marie-Noëlle |
description | African rice gall midge (AfRGM) is one of the most destructive pests of irrigated and lowland African ecologies. This study aimed to identify the quantitative trait loci (QTL) associated with AfRGM pest incidence and resistance in three independent bi-parental rice populations (ITA306xBW348-1, ITA306xTOG7106 and ITA306xTOS14519), and to conduct meta QTL (mQTL) analysis to explore whether any genomic regions are conserved across different genetic backgrounds. Composite interval mapping (CIM) conducted on the three populations independently uncovered a total of 28 QTLs associated with pest incidence (12) and pest severity (16). The number of QTLs per population associated with AfRGM resistance varied from three in the ITA306xBW348-1 population to eight in the ITA306xTOG7106 population. Each QTL individually explained 1.3 to 34.1% of the phenotypic variance. The major genomic region for AfRGM resistance had a LOD score and R2 of 60.0 and 34.1% respectively, and mapped at 111 cM on chromosome 4 (qAfrGM4) in the ITA306xTOS14519 population. The meta-analysis reduced the number of QTLs from 28 to 17 mQTLs, each explaining 1.3 to 24.5% of phenotypic variance, and narrowed the confidence intervals by 2.2 cM. There was only one minor effect mQTL on chromosome 1 that was common in the TOS14519 and TOG7106 genetic backgrounds; all other mQTLs were background specific. We are currently fine-mapping and validating the major effect genomic region on chromosome 4 (qAfRGM4). This is the first report in mapping the genomic regions associated with the AfRGM resistance, and will be highly useful for rice breeders. |
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This study aimed to identify the quantitative trait loci (QTL) associated with AfRGM pest incidence and resistance in three independent bi-parental rice populations (ITA306xBW348-1, ITA306xTOG7106 and ITA306xTOS14519), and to conduct meta QTL (mQTL) analysis to explore whether any genomic regions are conserved across different genetic backgrounds. Composite interval mapping (CIM) conducted on the three populations independently uncovered a total of 28 QTLs associated with pest incidence (12) and pest severity (16). The number of QTLs per population associated with AfRGM resistance varied from three in the ITA306xBW348-1 population to eight in the ITA306xTOG7106 population. Each QTL individually explained 1.3 to 34.1% of the phenotypic variance. The major genomic region for AfRGM resistance had a LOD score and R2 of 60.0 and 34.1% respectively, and mapped at 111 cM on chromosome 4 (qAfrGM4) in the ITA306xTOS14519 population. The meta-analysis reduced the number of QTLs from 28 to 17 mQTLs, each explaining 1.3 to 24.5% of phenotypic variance, and narrowed the confidence intervals by 2.2 cM. There was only one minor effect mQTL on chromosome 1 that was common in the TOS14519 and TOG7106 genetic backgrounds; all other mQTLs were background specific. We are currently fine-mapping and validating the major effect genomic region on chromosome 4 (qAfRGM4). This is the first report in mapping the genomic regions associated with the AfRGM resistance, and will be highly useful for rice breeders.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0160749</identifier><identifier>PMID: 27508500</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Africa ; Agricultural production ; Agriculture ; Analysis ; Animals ; Bioinformatics ; Biology ; Biology and Life Sciences ; Chromosome 1 ; Chromosome 4 ; Chromosomes, Plant ; Confidence intervals ; Crop science ; Diptera ; Ecological monitoring ; Gall ; Gene loci ; Gene mapping ; Genetic aspects ; Genetics ; Genetics, Population ; Genomics ; Germplasm ; Incidence ; Mapping ; Meta-analysis ; Orseolia oryzivora ; Oryza - genetics ; Oryza - physiology ; Oryza glaberrima ; Oryza sativa ; Pests ; Phenotype ; Physical Sciences ; Physiological aspects ; Plant resistance ; Polymerase Chain Reaction - methods ; Polymorphism, Single Nucleotide ; Population ; Populations ; Quantitative genetics ; Quantitative Trait Loci ; Research and Analysis Methods ; Rice ; Studies</subject><ispartof>PloS one, 2016-08, Vol.11 (8), p.e0160749-e0160749</ispartof><rights>COPYRIGHT 2016 Public Library of Science</rights><rights>This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication: https://creativecommons.org/publicdomain/zero/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c725t-1a5bcea17699e7e825610dd1a0353f2e0490f780268480db87302bac879756223</citedby><cites>FETCH-LOGICAL-c725t-1a5bcea17699e7e825610dd1a0353f2e0490f780268480db87302bac879756223</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/1812538047/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/1812538047?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,25753,27924,27925,37012,37013,44590,53791,53793,75126</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27508500$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Kulwal, Pawan L.</contributor><creatorcontrib>Yao, Nasser</creatorcontrib><creatorcontrib>Lee, Cheng-Ruei</creatorcontrib><creatorcontrib>Semagn, Kassa</creatorcontrib><creatorcontrib>Sow, Mounirou</creatorcontrib><creatorcontrib>Nwilene, Francis</creatorcontrib><creatorcontrib>Kolade, Olufisayo</creatorcontrib><creatorcontrib>Bocco, Roland</creatorcontrib><creatorcontrib>Oyetunji, Olumoye</creatorcontrib><creatorcontrib>Mitchell-Olds, Thomas</creatorcontrib><creatorcontrib>Ndjiondjop, Marie-Noëlle</creatorcontrib><title>QTL Mapping in Three Rice Populations Uncovers Major Genomic Regions Associated with African Rice Gall Midge Resistance</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>African rice gall midge (AfRGM) is one of the most destructive pests of irrigated and lowland African ecologies. 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The meta-analysis reduced the number of QTLs from 28 to 17 mQTLs, each explaining 1.3 to 24.5% of phenotypic variance, and narrowed the confidence intervals by 2.2 cM. There was only one minor effect mQTL on chromosome 1 that was common in the TOS14519 and TOG7106 genetic backgrounds; all other mQTLs were background specific. We are currently fine-mapping and validating the major effect genomic region on chromosome 4 (qAfRGM4). This is the first report in mapping the genomic regions associated with the AfRGM resistance, and will be highly useful for rice breeders.</description><subject>Africa</subject><subject>Agricultural production</subject><subject>Agriculture</subject><subject>Analysis</subject><subject>Animals</subject><subject>Bioinformatics</subject><subject>Biology</subject><subject>Biology and Life Sciences</subject><subject>Chromosome 1</subject><subject>Chromosome 4</subject><subject>Chromosomes, Plant</subject><subject>Confidence intervals</subject><subject>Crop science</subject><subject>Diptera</subject><subject>Ecological monitoring</subject><subject>Gall</subject><subject>Gene loci</subject><subject>Gene mapping</subject><subject>Genetic aspects</subject><subject>Genetics</subject><subject>Genetics, Population</subject><subject>Genomics</subject><subject>Germplasm</subject><subject>Incidence</subject><subject>Mapping</subject><subject>Meta-analysis</subject><subject>Orseolia oryzivora</subject><subject>Oryza - genetics</subject><subject>Oryza - physiology</subject><subject>Oryza glaberrima</subject><subject>Oryza sativa</subject><subject>Pests</subject><subject>Phenotype</subject><subject>Physical Sciences</subject><subject>Physiological aspects</subject><subject>Plant resistance</subject><subject>Polymerase Chain Reaction - methods</subject><subject>Polymorphism, Single Nucleotide</subject><subject>Population</subject><subject>Populations</subject><subject>Quantitative genetics</subject><subject>Quantitative Trait Loci</subject><subject>Research and Analysis Methods</subject><subject>Rice</subject><subject>Studies</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNqNk11v0zAUhiMEYmPwDxBEQkJw0eKPxE5ukKoJSqVOg7Jxa7nOSerKtYudbPDvcdtsatAuJl_Ysp_z-vj1OUnyGqMxphx_WrvOW2nGW2dhjDBDPCufJKe4pGTECKJPj9YnyYsQ1gjltGDseXJCeI6KHKHT5PbH1Ty9kNuttk2qbXq18gDpQitIv7ttZ2SrnQ3ptVXuBnyI6Nr5dArWbbRKF9DsjychOKVlC1V6q9tVOqm9VtIedKbSmPRCV03UhaBDK62Cl8mzWpoAr_r5LLn--uXq_NtofjmdnU_mI8VJ3o6wzJcKJOasLIFDQXKGUVVhiWhOawIoK1HNC0RYkRWoWhacIrKUquAlzxkh9Cx5e9DdGhdE71kQuMAkmoEyHonZgaicXIut1xvp_wontdhvON8I6VutDAiOccVBclzldYYRLivOsGIkx4QSriBqfe5v65YbqBTY1kszEB2eWL0SjbsRWVkgRHfJfOgFvPvdQWjFRgcFxkgLrtvnnXNEKX4UiklJGcki-u4_9GEjeqqR8a3a1i6mqHaiYpIxlEWPOYvU-AEqjgpiRcRarHXcHwR8HAREpoU_bSO7EMTs5-Lx7OWvIfv-iF2BNO0qONPtC3YIZgdQeReCh_r-PzASu1a6c0PsWkn0rRTD3hz_5X3QXe_Qf6OIFiA</recordid><startdate>20160810</startdate><enddate>20160810</enddate><creator>Yao, Nasser</creator><creator>Lee, Cheng-Ruei</creator><creator>Semagn, Kassa</creator><creator>Sow, Mounirou</creator><creator>Nwilene, Francis</creator><creator>Kolade, Olufisayo</creator><creator>Bocco, Roland</creator><creator>Oyetunji, Olumoye</creator><creator>Mitchell-Olds, Thomas</creator><creator>Ndjiondjop, Marie-Noëlle</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><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>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>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></search><sort><creationdate>20160810</creationdate><title>QTL Mapping in Three Rice Populations Uncovers Major Genomic Regions Associated with African Rice Gall Midge Resistance</title><author>Yao, Nasser ; Lee, Cheng-Ruei ; Semagn, Kassa ; Sow, Mounirou ; Nwilene, Francis ; Kolade, Olufisayo ; Bocco, Roland ; Oyetunji, Olumoye ; Mitchell-Olds, Thomas ; Ndjiondjop, Marie-Noëlle</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c725t-1a5bcea17699e7e825610dd1a0353f2e0490f780268480db87302bac879756223</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Africa</topic><topic>Agricultural production</topic><topic>Agriculture</topic><topic>Analysis</topic><topic>Animals</topic><topic>Bioinformatics</topic><topic>Biology</topic><topic>Biology and Life Sciences</topic><topic>Chromosome 1</topic><topic>Chromosome 4</topic><topic>Chromosomes, Plant</topic><topic>Confidence intervals</topic><topic>Crop science</topic><topic>Diptera</topic><topic>Ecological monitoring</topic><topic>Gall</topic><topic>Gene loci</topic><topic>Gene mapping</topic><topic>Genetic aspects</topic><topic>Genetics</topic><topic>Genetics, Population</topic><topic>Genomics</topic><topic>Germplasm</topic><topic>Incidence</topic><topic>Mapping</topic><topic>Meta-analysis</topic><topic>Orseolia oryzivora</topic><topic>Oryza - 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This study aimed to identify the quantitative trait loci (QTL) associated with AfRGM pest incidence and resistance in three independent bi-parental rice populations (ITA306xBW348-1, ITA306xTOG7106 and ITA306xTOS14519), and to conduct meta QTL (mQTL) analysis to explore whether any genomic regions are conserved across different genetic backgrounds. Composite interval mapping (CIM) conducted on the three populations independently uncovered a total of 28 QTLs associated with pest incidence (12) and pest severity (16). The number of QTLs per population associated with AfRGM resistance varied from three in the ITA306xBW348-1 population to eight in the ITA306xTOG7106 population. Each QTL individually explained 1.3 to 34.1% of the phenotypic variance. The major genomic region for AfRGM resistance had a LOD score and R2 of 60.0 and 34.1% respectively, and mapped at 111 cM on chromosome 4 (qAfrGM4) in the ITA306xTOS14519 population. The meta-analysis reduced the number of QTLs from 28 to 17 mQTLs, each explaining 1.3 to 24.5% of phenotypic variance, and narrowed the confidence intervals by 2.2 cM. There was only one minor effect mQTL on chromosome 1 that was common in the TOS14519 and TOG7106 genetic backgrounds; all other mQTLs were background specific. We are currently fine-mapping and validating the major effect genomic region on chromosome 4 (qAfRGM4). This is the first report in mapping the genomic regions associated with the AfRGM resistance, and will be highly useful for rice breeders.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>27508500</pmid><doi>10.1371/journal.pone.0160749</doi><tpages>e0160749</tpages><oa>free_for_read</oa></addata></record> |
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recordid | cdi_plos_journals_1812538047 |
source | Open Access: PubMed Central; Publicly Available Content Database (Proquest) (PQ_SDU_P3) |
subjects | Africa Agricultural production Agriculture Analysis Animals Bioinformatics Biology Biology and Life Sciences Chromosome 1 Chromosome 4 Chromosomes, Plant Confidence intervals Crop science Diptera Ecological monitoring Gall Gene loci Gene mapping Genetic aspects Genetics Genetics, Population Genomics Germplasm Incidence Mapping Meta-analysis Orseolia oryzivora Oryza - genetics Oryza - physiology Oryza glaberrima Oryza sativa Pests Phenotype Physical Sciences Physiological aspects Plant resistance Polymerase Chain Reaction - methods Polymorphism, Single Nucleotide Population Populations Quantitative genetics Quantitative Trait Loci Research and Analysis Methods Rice Studies |
title | QTL Mapping in Three Rice Populations Uncovers Major Genomic Regions Associated with African Rice Gall Midge Resistance |
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