Plant & Animal Genome VI Conference Plant & Animal Genome VI Conference
W38
Forest Biotechnology Group, Department of Forestry, Box 8008, North Carolina State University, Raleigh, NC 27695-8008
The megagametophyte is a haploid nutritive tissue surrounding the embryo in the mature seed of gymnosperms, developing from a haploid megaspore. Conifers are one of the most important groups of gymnosperms in both commercial and environmental aspects. Although conventional quantitative genetic methods have contributed substantially to genetic improvement of coniferous species, its further role is limited by several biological characteristics. The quantitative trait locus (QTL) mapping method based on molecular markers opens a new avenue to break selection limit of conifers. Because it is haploid and independent of the paternal genotype, the megagametophyte as the source of marker-QTL linkage analysis has many biological and statistical advantages. In this paper, we explore the statistical procedures for QTL mapping using megagametophytes derived from an open-pollinated, heterozygous tree within the framework of Zengís (1993, 1994) composite interval mapping method. It is demonstrated that megagametophyte mapping can provide unbiased estimates for six QTL parameters including the additive effect, the dominant effect, the population mean, the chromosomal location of the QTL in the interval, the population frequency of the QTL alleles, and the residual variance within the QTL genotypes. Also, the estimation of each of these parameters from megagametophyte mapping is not affected by marker-allelic frequencies in the population, which is advantageous compared to a QTL mapping strategy that uses diploid tissues and a half-sib design, developed by Mackinnon and Weller (1995). Since the mother coniferous tree from which seeds are collected to map QTL may undergo both selfing and outcrossing, the influences of progeny composition (selfing and outcrossing) and QTL-allelic frequency in the outcrossing progeny are discussed for the estimation of QTL parameters by computer simulation studies.