Mapping genetic loci for iron deficiency chlorosis in soybean
The objective of this study was to map genes controlling iron deficiency chlorosis in two intraspecific soybean [Glycine max (L.) Merrill] populations. Chlorosis symptoms were evaluated by visual scores and spectrometric chlorophyll determinations at the V4 stage (third trifoliolate leaf fully devel...
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Veröffentlicht in: | Molecular breeding 1997-06, Vol.3 (3), p.219-229 |
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description | The objective of this study was to map genes controlling iron deficiency chlorosis in two intraspecific soybean [Glycine max (L.) Merrill] populations. Chlorosis symptoms were evaluated by visual scores and spectrometric chlorophyll determinations at the V4 stage (third trifoliolate leaf fully developed) in the field in 1993, and at V2 (first trifoliolate leaf fully developed) and V4 stages in 1994. A total of 89 RFLP and 10 SSR markers in the Pride B216 x A15 population, and 82 RFLP, 14 SSR and 1 morphological I (hilum color) markers in the Anoka x A7 population were used to map quantitative trait loci (QTL) affecting iron deficiency chlorosis. QTL with minor effects were detected on six linkage groups of the Pride B216 x A15 population, suggesting a typical polygene mechanism. In contrast, in the Anoka x A7 population, one QTL contributed an average of 72.7% of the visual score variation and 68.8% of the chlorophyll concentration variation and was mapped on linkage group N. Another QTL for visual score variation, and one for chlorophyll concentration variation were detected on linkage groups A1 and I, respectively. Due to the large LOD score and major genetic effect of the QTL on linkage group N, the quantitative data was reclassified into qualitative data fitting a one major gene model according to the means of the QTL genotypic classes. The major gene was mapped in the same interval of linkage group N using both visual scores and chlorophyll concentrations, thus verifying that one major gene is involved in segregation for iron chlorosis deficiency in the Anoka x A7 population. This study supported a previous hypothesis that two separate genetic mechanisms control iron deficiency in soybean. |
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(Iowa State Univ., Ames, IA (USA). Dept. of Agronomy) ; Shoemaker, R</creator><creatorcontrib>Lin, S. (Iowa State Univ., Ames, IA (USA). Dept. of Agronomy) ; Shoemaker, R</creatorcontrib><description>The objective of this study was to map genes controlling iron deficiency chlorosis in two intraspecific soybean [Glycine max (L.) Merrill] populations. Chlorosis symptoms were evaluated by visual scores and spectrometric chlorophyll determinations at the V4 stage (third trifoliolate leaf fully developed) in the field in 1993, and at V2 (first trifoliolate leaf fully developed) and V4 stages in 1994. A total of 89 RFLP and 10 SSR markers in the Pride B216 x A15 population, and 82 RFLP, 14 SSR and 1 morphological I (hilum color) markers in the Anoka x A7 population were used to map quantitative trait loci (QTL) affecting iron deficiency chlorosis. QTL with minor effects were detected on six linkage groups of the Pride B216 x A15 population, suggesting a typical polygene mechanism. In contrast, in the Anoka x A7 population, one QTL contributed an average of 72.7% of the visual score variation and 68.8% of the chlorophyll concentration variation and was mapped on linkage group N. Another QTL for visual score variation, and one for chlorophyll concentration variation were detected on linkage groups A1 and I, respectively. Due to the large LOD score and major genetic effect of the QTL on linkage group N, the quantitative data was reclassified into qualitative data fitting a one major gene model according to the means of the QTL genotypic classes. The major gene was mapped in the same interval of linkage group N using both visual scores and chlorophyll concentrations, thus verifying that one major gene is involved in segregation for iron chlorosis deficiency in the Anoka x A7 population. This study supported a previous hypothesis that two separate genetic mechanisms control iron deficiency in soybean.</description><identifier>ISSN: 1380-3743</identifier><identifier>EISSN: 1572-9788</identifier><identifier>DOI: 10.1023/A:1009637320805</identifier><language>eng</language><publisher>Dordrecht: Springer Nature B.V</publisher><subject>CARENCE EN OLIGOELEMENT ; CARTE GENETIQUE ; Chlorophyll ; CHLOROSE ; CHLOROSIS ; CLOROSIS ; DEFICIENCIA DE OLIGOELEMENTOS ; FER ; Gene mapping ; GENETIC MAPS ; GENETICA ; GENETICS ; GENETIQUE ; GLYCINE MAX ; HIERRO ; IRON ; Iron deficiency ; Leaves ; LOCI ; LOCUS ; MAPAS GENETICOS ; Mapping ; Markers ; Molecular biology ; Nutrient deficiency ; Plant biology ; Population ; Population studies ; Qualitative analysis ; Quantitative trait loci ; Soybeans ; Spectrometry ; TRACE ELEMENT DEFICIENCIES</subject><ispartof>Molecular breeding, 1997-06, Vol.3 (3), p.219-229</ispartof><rights>Molecular Breeding is a copyright of Springer, (1997). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27915,27916</link.rule.ids></links><search><creatorcontrib>Lin, S. (Iowa State Univ., Ames, IA (USA). Dept. of Agronomy)</creatorcontrib><creatorcontrib>Shoemaker, R</creatorcontrib><title>Mapping genetic loci for iron deficiency chlorosis in soybean</title><title>Molecular breeding</title><description>The objective of this study was to map genes controlling iron deficiency chlorosis in two intraspecific soybean [Glycine max (L.) Merrill] populations. Chlorosis symptoms were evaluated by visual scores and spectrometric chlorophyll determinations at the V4 stage (third trifoliolate leaf fully developed) in the field in 1993, and at V2 (first trifoliolate leaf fully developed) and V4 stages in 1994. A total of 89 RFLP and 10 SSR markers in the Pride B216 x A15 population, and 82 RFLP, 14 SSR and 1 morphological I (hilum color) markers in the Anoka x A7 population were used to map quantitative trait loci (QTL) affecting iron deficiency chlorosis. QTL with minor effects were detected on six linkage groups of the Pride B216 x A15 population, suggesting a typical polygene mechanism. In contrast, in the Anoka x A7 population, one QTL contributed an average of 72.7% of the visual score variation and 68.8% of the chlorophyll concentration variation and was mapped on linkage group N. Another QTL for visual score variation, and one for chlorophyll concentration variation were detected on linkage groups A1 and I, respectively. Due to the large LOD score and major genetic effect of the QTL on linkage group N, the quantitative data was reclassified into qualitative data fitting a one major gene model according to the means of the QTL genotypic classes. The major gene was mapped in the same interval of linkage group N using both visual scores and chlorophyll concentrations, thus verifying that one major gene is involved in segregation for iron chlorosis deficiency in the Anoka x A7 population. This study supported a previous hypothesis that two separate genetic mechanisms control iron deficiency in soybean.</description><subject>CARENCE EN OLIGOELEMENT</subject><subject>CARTE GENETIQUE</subject><subject>Chlorophyll</subject><subject>CHLOROSE</subject><subject>CHLOROSIS</subject><subject>CLOROSIS</subject><subject>DEFICIENCIA DE OLIGOELEMENTOS</subject><subject>FER</subject><subject>Gene mapping</subject><subject>GENETIC MAPS</subject><subject>GENETICA</subject><subject>GENETICS</subject><subject>GENETIQUE</subject><subject>GLYCINE MAX</subject><subject>HIERRO</subject><subject>IRON</subject><subject>Iron deficiency</subject><subject>Leaves</subject><subject>LOCI</subject><subject>LOCUS</subject><subject>MAPAS GENETICOS</subject><subject>Mapping</subject><subject>Markers</subject><subject>Molecular biology</subject><subject>Nutrient deficiency</subject><subject>Plant biology</subject><subject>Population</subject><subject>Population studies</subject><subject>Qualitative analysis</subject><subject>Quantitative trait loci</subject><subject>Soybeans</subject><subject>Spectrometry</subject><subject>TRACE ELEMENT DEFICIENCIES</subject><issn>1380-3743</issn><issn>1572-9788</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1997</creationdate><recordtype>article</recordtype><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNpdkE1LAzEYhIMoWKtnT0JA8Lb6vsnmS_AgxS-oetHzkk2TmrImddMe-u8N1JOnmcPDMDOEnCNcIzB-c3-LAEZyxRloEAdkgkKxxiitD6vnGhquWn5MTkpZAYAyUk7I3atdr2Na0qVPfhMdHbKLNOSRxjEnuvAhuuiT21H3NeQxl1hoTLTkXe9tOiVHwQ7Fn_3plHw-PnzMnpv5-9PL7H7eBMbbTWNNrzSCNswZDdyrXgRUSrRGGS4VIPeyxQC6twsP0rHeOuvAy7pEWy_4lFztc9dj_tn6sum-Y3F-GGzyeVs6lICMS6zg5T9wlbdjqt06xoQRDEHqSl3sqWBzZ5djLN3bHE3tBmjql7_NQV89</recordid><startdate>19970601</startdate><enddate>19970601</enddate><creator>Lin, S. (Iowa State Univ., Ames, IA (USA). Dept. of Agronomy)</creator><creator>Shoemaker, R</creator><general>Springer Nature B.V</general><scope>FBQ</scope><scope>3V.</scope><scope>7X2</scope><scope>8FE</scope><scope>8FH</scope><scope>8FK</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>LK8</scope><scope>M0K</scope><scope>M7P</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope><scope>RC3</scope></search><sort><creationdate>19970601</creationdate><title>Mapping genetic loci for iron deficiency chlorosis in soybean</title><author>Lin, S. (Iowa State Univ., Ames, IA (USA). Dept. of Agronomy) ; Shoemaker, R</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-f234t-a9b7810892c9803e7b5f17754979367013e641f08bade06c2bacac0e62088ae53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1997</creationdate><topic>CARENCE EN OLIGOELEMENT</topic><topic>CARTE GENETIQUE</topic><topic>Chlorophyll</topic><topic>CHLOROSE</topic><topic>CHLOROSIS</topic><topic>CLOROSIS</topic><topic>DEFICIENCIA DE OLIGOELEMENTOS</topic><topic>FER</topic><topic>Gene mapping</topic><topic>GENETIC MAPS</topic><topic>GENETICA</topic><topic>GENETICS</topic><topic>GENETIQUE</topic><topic>GLYCINE MAX</topic><topic>HIERRO</topic><topic>IRON</topic><topic>Iron deficiency</topic><topic>Leaves</topic><topic>LOCI</topic><topic>LOCUS</topic><topic>MAPAS GENETICOS</topic><topic>Mapping</topic><topic>Markers</topic><topic>Molecular biology</topic><topic>Nutrient deficiency</topic><topic>Plant biology</topic><topic>Population</topic><topic>Population studies</topic><topic>Qualitative analysis</topic><topic>Quantitative trait loci</topic><topic>Soybeans</topic><topic>Spectrometry</topic><topic>TRACE ELEMENT DEFICIENCIES</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lin, S. (Iowa State Univ., Ames, IA (USA). Dept. of Agronomy)</creatorcontrib><creatorcontrib>Shoemaker, R</creatorcontrib><collection>AGRIS</collection><collection>ProQuest Central (Corporate)</collection><collection>Agricultural Science Collection</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</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>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Agricultural Science Database</collection><collection>Biological Science 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>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><jtitle>Molecular breeding</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lin, S. (Iowa State Univ., Ames, IA (USA). Dept. of Agronomy)</au><au>Shoemaker, R</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Mapping genetic loci for iron deficiency chlorosis in soybean</atitle><jtitle>Molecular breeding</jtitle><date>1997-06-01</date><risdate>1997</risdate><volume>3</volume><issue>3</issue><spage>219</spage><epage>229</epage><pages>219-229</pages><issn>1380-3743</issn><eissn>1572-9788</eissn><abstract>The objective of this study was to map genes controlling iron deficiency chlorosis in two intraspecific soybean [Glycine max (L.) Merrill] populations. Chlorosis symptoms were evaluated by visual scores and spectrometric chlorophyll determinations at the V4 stage (third trifoliolate leaf fully developed) in the field in 1993, and at V2 (first trifoliolate leaf fully developed) and V4 stages in 1994. A total of 89 RFLP and 10 SSR markers in the Pride B216 x A15 population, and 82 RFLP, 14 SSR and 1 morphological I (hilum color) markers in the Anoka x A7 population were used to map quantitative trait loci (QTL) affecting iron deficiency chlorosis. QTL with minor effects were detected on six linkage groups of the Pride B216 x A15 population, suggesting a typical polygene mechanism. In contrast, in the Anoka x A7 population, one QTL contributed an average of 72.7% of the visual score variation and 68.8% of the chlorophyll concentration variation and was mapped on linkage group N. Another QTL for visual score variation, and one for chlorophyll concentration variation were detected on linkage groups A1 and I, respectively. Due to the large LOD score and major genetic effect of the QTL on linkage group N, the quantitative data was reclassified into qualitative data fitting a one major gene model according to the means of the QTL genotypic classes. The major gene was mapped in the same interval of linkage group N using both visual scores and chlorophyll concentrations, thus verifying that one major gene is involved in segregation for iron chlorosis deficiency in the Anoka x A7 population. This study supported a previous hypothesis that two separate genetic mechanisms control iron deficiency in soybean.</abstract><cop>Dordrecht</cop><pub>Springer Nature B.V</pub><doi>10.1023/A:1009637320805</doi><tpages>11</tpages></addata></record> |
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subjects | CARENCE EN OLIGOELEMENT CARTE GENETIQUE Chlorophyll CHLOROSE CHLOROSIS CLOROSIS DEFICIENCIA DE OLIGOELEMENTOS FER Gene mapping GENETIC MAPS GENETICA GENETICS GENETIQUE GLYCINE MAX HIERRO IRON Iron deficiency Leaves LOCI LOCUS MAPAS GENETICOS Mapping Markers Molecular biology Nutrient deficiency Plant biology Population Population studies Qualitative analysis Quantitative trait loci Soybeans Spectrometry TRACE ELEMENT DEFICIENCIES |
title | Mapping genetic loci for iron deficiency chlorosis in soybean |
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