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  • 1
    ISSN: 1432-2242
    Keywords: Quantitative trait locus ; QTL ; Disease resistance ; Polygenic
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract A major partial-resistance locus to the soybean cyst nematode (Heterodera glycines Ichinohe; SCN) was identified on linkage group ‘G’ of soybean [Glycine max (L.) Merr.] using restriction fragment length polymorphisms (RFLPs). This locus explained 51.4% (LOD=10.35) of the total phenotypic variation in disease response in soybean Plant Introduction (PI) 209332, 52.7% (LOD=15.58) in PI 90763, 40.0% (LOD=10.50) in PI 88788, and 28.1% (LOD=6.94) in ‘Peking’. Initially, the region around this major resistance locus was poorly populated with DNA markers. To increase marker density in this genomic region, first random, and later targeted, comparative mapping with RFLPs from mungbean [Vigna radiata (L.) R. Wilcz.] and common bean (Phaseolus vulgaris L.) was performed, eventually leading to one RFLP marker every 2.6 centimorgans (cM). Even with this marker density, the inability to resolve SCN disease response into discrete Mendelian categories posed a major limitation to mapping. Thus, qualitative scoring of SCN disease response was carried out in an F5∶6 recombinant inbred population derived from ‘Evans’xPI 209332 using a 30% disease index cut-off for resistance. Using the computer program JoinMap, an integrated map of the region of interest was created, placing the SCN resistance locus 4.6 cM from RFLP marker B53 and 2.8 cM from Bng30. This study demonstrates how a combination of molecularmapping strategies, including comparative genome analysis, join mapping, and qualitative scoring of a quantitative trait, potentially provide the necessary tools for high-resolution mapping around a quantitative-trait locus.
    Type of Medium: Electronic Resource
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    ISSN: 1432-2242
    Keywords: Key words Quantitative trait locus ; QTL ; Disease resistance ; Polygenic
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology
    Notes: Abstract A major partial-resistance locus to the soybean cyst nematode (Heterodera glycines Ichinohe; SCN) was identified on linkage group `G' of soybean [Glycine max (L.) Merr.] using restriction fragment length polymorphisms (RFLPs). This locus explained 51.4% (LOD=10.35) of the total phenotypic variation in disease response in soybean Plant Introduction (PI) 209332, 52.7% (LOD=15.58) in PI 90763, 40.0% (LOD=10.50) in PI 88788, and 28.1% (LOD=6.94) in `Peking'. Initially, the region around this major resistance locus was poorly populated with DNA markers. To increase marker density in this genomic region, first random, and later targeted, comparative mapping with RFLPs from mungbean [Vigna radiata (L.) R. Wilcz.] and common bean (Phaseolus vulgaris L.) was performed, eventually leading to one RFLP marker every 2.6 centimorgans (cM). Even with this marker density, the inability to resolve SCN disease response into discrete Mendelian categories posed a major limitation to mapping. Thus, qualitative scoring of SCN disease response was carried out in an F5:6 recombinant inbred population derived from `Evans'×PI 209332 using a 30% disease index cut-off for resistance. Using the computer program JoinMap, an integrated map of the region of interest was created, placing the SCN resistance locus 4.6 cM from RFLP marker B53 and 2.8 cM from Bng30. This study demonstrates how a combination of molecular-mapping strategies, including comparative genome analysis, join mapping, and qualitative scoring of a quantitative trait, potentially provide the necessary tools for high-resolution mapping around a quantitative-trait locus.
    Type of Medium: Electronic Resource
    Library Location Call Number Volume/Issue/Year Availability
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  • 3
    Electronic Resource
    Electronic Resource
    Springer
    Journal of materials science 28 (1993), S. 3879-3884 
    ISSN: 1573-4803
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Abstract Confocal microscopy provides a convenient means of acquiring three-dimensional descriptions of objects. A new technique exploits the capability of confocal microscopy to quantify rough surfaces. The microscope “optically” sections the surface, and a computer transforms a series of sections into digital images and a topographic map. Using a straightforward algorithm, the computer analyses the topographic map to derive a roughness parameter that characterizes the texture of the surface.
    Type of Medium: Electronic Resource
    Library Location Call Number Volume/Issue/Year Availability
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