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A E Melchinger

Publications and source records attributed to A E Melchinger.

4 recordsLinked to original sources
PubMed1999

High-resolution mapping of loci conferring resistance to sugarcane mosaic virus in maize using RFLP, SSR, and AFLP markers.

Sugarcane mosaic virus (SCMV) is one of the most important virus diseases of maize in Europe. Genetic analysis on backcross five (BC5) progeny derived from the cross FAP1360A (resistant) x F7 (susceptible) confirmed that at least two dominant genes, Scm1 and Scm2, are required for resistance to SCMV in the progeny of this cross. With the aid of RFLP and SSR marker analyses, Scm1 was mapped in the region of 8.7 cM between the nucleolus organizer region (nor) and RFLP marker bnl6.29 on the short arm of chromosome 6, while Scm2 was mapped to an interval of 26.8 cM flanked by the RFLP markers umc92 and umc102 near the centromere region of chromosome 3. Both chromosome regions were further enriched for AFLP markers by successful application of a bulked segregant analysis to this oligogenic trait. A total of 23 linked AFLP markers were identified, clustered in chromosome regions adjacent to either Scm1 or Scm2. Seven AFLP markers linked to Scm1 resided within the nor-bnl6.29 interval, and one of them, E3M8-1, showed no recombination with Scm1. Three AFLP markers linked to Scm2 are located between umc92 and umc102.

Chromosome Mapping↗
PubMed1998

Quantitative trait locus (QTL) mapping using different testers and independent population samples in maize reveals low power of QTL detection and large bias in estimates of QTL effects.

The efficiency of marker-assisted selection (MAS) depends on the power of quantitative trait locus (QTL) detection and unbiased estimation of QTL effects. Two independent samples N = 344 and 107 of F2 plants were genotyped for 89 RFLP markers. For each sample, testcross (TC) progenies of the corresponding F3 lines with two testers were evaluated in four environments. QTL for grain yield and other agronomically important traits were mapped in both samples. QTL effects were estimated from the same data as used for detection and mapping of QTL (calibration) and, based on QTL positions from calibration, from the second, independent sample (validation). For all traits and both testers we detected a total of 107 QTL with N = 344, and 39 QTL with N = 107, of which only 20 were in common. Consistency of QTL effects across testers was in agreement with corresponding genotypic correlations between the two TC series. Most QTL displayed no significant QTL x environment nor epistatic interactions. Estimates of the proportion of the phenotypic and genetic variance explained by QTL were considerably reduced when derived from the independent validation sample as opposed to estimates from the calibration sample. We conclude that, unless QTL effects are estimated from an independent sample, they can be inflated, resulting in an overly optimistic assessment of the efficiency of MAS.

Chromosome Mapping↗
PubMed1996

A general algorithm to compute multilocus genotype frequencies under various mating systems.

This paper provides a general method to derive algebraic expressions of genotype frequencies for multiple loci under various mating systems, including random mating, back-crossing, selfing, and full-sib mating. For each mating system, general equations are presented. In the case of three loci, comprehensive tables provide recurrence equations for genotype frequencies under random or self mating, and expected genotype frequencies after two generations of full-sib mating. Our results should prove useful in genetic linkage analysis.

Algorithms↗