Browsing by Author "Kasha, K.J."

Now showing 1 - 1 of 1
  • Thumbnail Image
    Item
    Regions of the genome that affect agronomic performance in two-row barley
    (Crop Science, 1996) Steffenson, Brian; Tinker, N.A.; Mather, D.E.; Rossnagel, B.G.; Kasha, K.J.; Kleinhofs, A.; Hayes, P.M.; Falk, D.E.; Ferguson, T.; Shugar, L.P.; Legge, W.G.; Irvine, R.B.; Choo, T.M.; Briggs, K.G.; Ullrich, S.E.; Franckowiak, J.D.; Blake, T.K.; Graf, R.J.; Dofing, S.M.; Saghai Maroof, M.A.; Scoles, G.J.; Hoffman, D.; Dahleen, L.S.; Kilian, A.; Chen, F.; Biyashev, R.M.; Kudrna, D.A.
    Quantitative trait locus (QTL) main effects and QTL by environment (QTL × E) interactions for seven agronomic traits (grain yield, days to heading, days to maturity, plant height, lodging severity, kernel weight, and test weight) were investigated in a two-row barley (Hordeum vulgare L.) cross, Harrington/TR306. A 127-point base map was constructed from markers (mostly RFLP) scored in 146 random double-haploid (DH) lines from the Harrington/TR306 cross. Field experiments involving the two parents and 145 random DH lines were grown in 1992 and/or 1993 at 17 locations in North America. Analysis of QTL was based on simple and composite interval mapping. Primary QTL were declared at positions where both methods gave evidence for QTL. The number of primary QTL ranged from three to six per trait, collectively explaining 34 to 52% of the genetic variance. None of these primary QTL showed major effects, but many showed effects that were consistent across environments. The addition of secondary QTL gave models that explained 39 to 80% of the genetic variance. The QTL were dispersed throughout the barley genome and some were detected in regions where QTL have been found in previous studies. Eight chromosome regions contained pleiotropic loci and/or linked clusters of loci that affected multiple traits. One region on chromosome 7 affected all traits except days to heading. This study was an intensive effort to evaluate QTL in a narrow-base population grown in a large set of environments. The results reveal the types and distributions of QTL effects manipulated by plant breeders and provide opportunities for future testing of marker-assisted selection.