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ARS Home » Midwest Area » Madison, Wisconsin » Cereal Crops Research » Research » Publications at this Location » Publication #102901
Title: BARLEY MALTING QUALITY QTLS COMPARED ACROSS MAPPING POPULATIONS

Author
item ZALE, J - WASHINGTON STATE UNIV
item CLANCY, J - WASHINGTON STATE UNIV
item Jones, Berne
item HAYES, P - OREGON STATE UNIVERSITY
item ULLRICH, S - WASHINGTON STATE UNIV.

Submitted to: Barley Newsletter
Publication Type: Abstract Only
Publication Acceptance Date: 7/10/1999
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Characters that affect malting quality are quantitatively inherited and variously influenced by the environment (E). Molecular technologies have opened the door for better understanding of these and other quantitatively inherited traits. Quantitative trait locus (QTL) analysis identifies chromosome regions, linked molecular markers, gene effects, QTL X E, and QTL X QTL interactions for a given trait. The objective of this study was to accumulate malting quality QTL mapping data published to date to update QTL designations in relation to consensus molecular markers. Additional molecular markers from an integrated map were used to anchor specific QTLs across mapping populations. A total of 156 malting quality QTLs representing 19 malting quality traits have been mapped in 9 mapping populations. QTL regions are spread across each of the seven barley chromosomes with concentrations within chromosomes 1 (7H) (ABC158-PSR129) and 5 (1H) (Act8-CDO99 and KgE33M59.222-ABC159c). Whereas, there is remarkable QTL conservation in some chromosome regions among crosses, some regions hold unique QTLs as well. There are many overlapping QTLs, especially of related traits. Malt extract QTLs are almost always coincident with component traits such as carbohydrate hydrolytic enzyme activities. Diastatic power QTLs are often associated with a- and/or b- am activity QTLs. Given that malting quality determinants are widely distributed across the barley genome, care must be taken in choosing QTLs for selection in breeding programs. In general, understanding of the truly complex quantitative traits is far from complete, and this will likely affect efficiency of molecular marker assisted selection for these traits.