Fine-mapping quantitative trait loci with a medium density marker panel: efficiency of population structures and comparison of linkage disequilibrium linkage analysis models
Identifieur interne : 005385 ( Main/Exploration ); précédent : 005384; suivant : 005386Fine-mapping quantitative trait loci with a medium density marker panel: efficiency of population structures and comparison of linkage disequilibrium linkage analysis models
Auteurs : Dana L. Roldan [Argentine] ; Hélène Gilbert [France] ; John M. Henshall [Australie] ; Andrés Legarra [France] ; Jean-Michel Elsen [France]Source :
- Genetics Research [ 0016-6723 ] ; 2012.
Abstract
Recently, a Haley–Knott-type regression method using combined linkage disequilibrium and linkage analyses (LDLA) was proposed to map quantitative trait loci (QTLs). Chromosome of 5 and 25 cM with 0·25 and 0·05 cM, respectively, between markers were simulated. The differences between the LDLA approaches with regard to QTL position accuracy were very limited, with a significantly better mean square error (MSE) with the LDLA regression (LDLA_reg) in sparse map cases; the contrary was observed, but not significantly, in dense map situations. The computing time required for the LDLA variance components (LDLA_vc) model was much higher than the LDLA_reg model. The precision of QTL position estimation was compared for four numbers of half-sib families, four different family sizes and two experimental designs (half-sibs, and full- and half-sibs). Regarding the number of families, MSE values were lowest for 15 or 50 half-sib families, differences not being significant. We observed that the greater the number of progenies per sire, the more accurate the QTL position. However, for a fixed population size, reducing the number of families (e.g. using a small number of large full-sib families) could lead to less accuracy of estimated QTL position.
Url:
DOI: 10.1017/S0016672312000407
PubMed: 22950902
PubMed Central: 3487687
Affiliations:
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Roldan</name><affiliation wicri:level="1"><nlm:aff id="aff001">Instituto de Genética CICVyA-INTA Castelar, cc 1712, Buenos Aires, Argentina</nlm:aff><country xml:lang="fr">Argentine</country><wicri:regionArea>Instituto de Genética CICVyA-INTA Castelar, cc 1712, Buenos Aires</wicri:regionArea><wicri:noRegion>Buenos Aires</wicri:noRegion></affiliation></author><author><name sortKey="Gilbert, Helene" sort="Gilbert, Helene" uniqKey="Gilbert H" first="Hélène" last="Gilbert">Hélène Gilbert</name><affiliation wicri:level="1"><nlm:aff id="aff002">INRA-Laboratoire de Génétique Cellulaire, Auzeville, B.P. 52627, 31326 Castanet Tolosan Cedex, France</nlm:aff><country xml:lang="fr">France</country><wicri:regionArea>INRA-Laboratoire de Génétique Cellulaire, Auzeville, B.P. 52627, 31326 Castanet Tolosan Cedex</wicri:regionArea><wicri:noRegion>31326 Castanet Tolosan Cedex</wicri:noRegion><wicri:noRegion>31326 Castanet Tolosan Cedex</wicri:noRegion></affiliation></author><author><name sortKey="Henshall, John M" sort="Henshall, John M" uniqKey="Henshall J" first="John M" last="Henshall">John M. 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Roldan</name><affiliation wicri:level="1"><nlm:aff id="aff001">Instituto de Genética CICVyA-INTA Castelar, cc 1712, Buenos Aires, Argentina</nlm:aff><country xml:lang="fr">Argentine</country><wicri:regionArea>Instituto de Genética CICVyA-INTA Castelar, cc 1712, Buenos Aires</wicri:regionArea><wicri:noRegion>Buenos Aires</wicri:noRegion></affiliation></author><author><name sortKey="Gilbert, Helene" sort="Gilbert, Helene" uniqKey="Gilbert H" first="Hélène" last="Gilbert">Hélène Gilbert</name><affiliation wicri:level="1"><nlm:aff id="aff002">INRA-Laboratoire de Génétique Cellulaire, Auzeville, B.P. 52627, 31326 Castanet Tolosan Cedex, France</nlm:aff><country xml:lang="fr">France</country><wicri:regionArea>INRA-Laboratoire de Génétique Cellulaire, Auzeville, B.P. 52627, 31326 Castanet Tolosan Cedex</wicri:regionArea><wicri:noRegion>31326 Castanet Tolosan Cedex</wicri:noRegion><wicri:noRegion>31326 Castanet Tolosan Cedex</wicri:noRegion></affiliation></author><author><name sortKey="Henshall, John M" sort="Henshall, John M" uniqKey="Henshall J" first="John M" last="Henshall">John M. Henshall</name><affiliation wicri:level="1"><nlm:aff id="aff003">CSIRO Livestock Industries FD McMaster Laboratory, Armidale, NSW 2350, Australia</nlm:aff><country xml:lang="fr">Australie</country><wicri:regionArea>CSIRO Livestock Industries FD McMaster Laboratory, Armidale, NSW 2350</wicri:regionArea><wicri:noRegion>NSW 2350</wicri:noRegion></affiliation></author><author><name sortKey="Legarra, Andres" sort="Legarra, Andres" uniqKey="Legarra A" first="Andrés" last="Legarra">Andrés Legarra</name><affiliation wicri:level="1"><nlm:aff id="aff004">INRA-SAGA Auzeville, B.P. 52627, 31326 Castanet Tolosan Cedex, France</nlm:aff><country xml:lang="fr">France</country><wicri:regionArea>INRA-SAGA Auzeville, B.P. 52627, 31326 Castanet Tolosan Cedex</wicri:regionArea><wicri:noRegion>31326 Castanet Tolosan Cedex</wicri:noRegion><wicri:noRegion>31326 Castanet Tolosan Cedex</wicri:noRegion></affiliation></author><author><name sortKey="Elsen, Jean Michel" sort="Elsen, Jean Michel" uniqKey="Elsen J" first="Jean-Michel" last="Elsen">Jean-Michel Elsen</name><affiliation wicri:level="1"><nlm:aff id="aff004">INRA-SAGA Auzeville, B.P. 52627, 31326 Castanet Tolosan Cedex, France</nlm:aff><country xml:lang="fr">France</country><wicri:regionArea>INRA-SAGA Auzeville, B.P. 52627, 31326 Castanet Tolosan Cedex</wicri:regionArea><wicri:noRegion>31326 Castanet Tolosan Cedex</wicri:noRegion><wicri:noRegion>31326 Castanet Tolosan Cedex</wicri:noRegion></affiliation></author></analytic><series><title level="j">Genetics Research</title><idno type="ISSN">0016-6723</idno><idno type="eISSN">1469-5073</idno><imprint><date when="2012">2012</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><title>Summary</title><p>Recently, a Haley–Knott-type regression method using combined linkage disequilibrium and linkage analyses (LDLA) was proposed to map quantitative trait loci (QTLs). Chromosome of 5 and 25 cM with 0·25 and 0·05 cM, respectively, between markers were simulated. The differences between the LDLA approaches with regard to QTL position accuracy were very limited, with a significantly better mean square error (MSE) with the LDLA regression (LDLA_reg) in sparse map cases; the contrary was observed, but not significantly, in dense map situations. The computing time required for the LDLA variance components (LDLA_vc) model was much higher than the LDLA_reg model. The precision of QTL position estimation was compared for four numbers of half-sib families, four different family sizes and two experimental designs (half-sibs, and full- and half-sibs). Regarding the number of families, MSE values were lowest for 15 or 50 half-sib families, differences not being significant. We observed that the greater the number of progenies per sire, the more accurate the QTL position. 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Dekkers</name></author></analytic></biblStruct></listBibl></div1></back></TEI><affiliations><list><country><li>Argentine</li><li>Australie</li><li>France</li></country></list><tree><country name="Argentine"><noRegion><name sortKey="Roldan, Dana L" sort="Roldan, Dana L" uniqKey="Roldan D" first="Dana L" last="Roldan">Dana L. Roldan</name></noRegion></country><country name="France"><noRegion><name sortKey="Gilbert, Helene" sort="Gilbert, Helene" uniqKey="Gilbert H" first="Hélène" last="Gilbert">Hélène Gilbert</name></noRegion><name sortKey="Elsen, Jean Michel" sort="Elsen, Jean Michel" uniqKey="Elsen J" first="Jean-Michel" last="Elsen">Jean-Michel Elsen</name><name sortKey="Legarra, Andres" sort="Legarra, Andres" uniqKey="Legarra A" first="Andrés" last="Legarra">Andrés Legarra</name></country><country name="Australie"><noRegion><name sortKey="Henshall, John M" sort="Henshall, John M" uniqKey="Henshall J" first="John M" last="Henshall">John M. 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