CROP BREEDING, GENETICS & CYTOLOGY SSR and Pedigree Analyses of Genetic Diversity among CIMMYT Wheat Lines Targeted to Different Megaenvironments S. Dreisigacker, P. Zhang, M. L. Warburton, M. Van Ginkel, D. Hoisington, M. Bohn, and A. E. Melchinger* ABSTRACT duced the concept of breeding for different MEs. A ME is defined as a large, not necessarily contiguous area, Improved bread wheat (Triticum aestivum L.) cultivars for diverse which usually encompasses more than one country and agroecological environments are important for success in the effort to increase food production. In the 1980s, CIMMYT introduced the is frequently transcontinental. It is characterized by sim- megaenvironment (ME) concept to breed wheats specifically adapted ilar biotic and abiotic stress conditions, cropping sys- to different areas. Our objective was to analyze the genetic diversity tems, and consumer demands (Rajaram et al., 1994). among 68 advanced CIMMYT wheat lines targeted to different MEs Twelve MEs have been classified, six of which are fo- by using 99 simple sequence repeats (SSRs) and the coefficient of cused on efficient selection of better-adapted spring parentage (COP). The average number of alleles detected was higher bread wheat, the dominant type of wheat in developing for the 47 genomic SSRs (5.4) than for the 52 SSRs derived from countries. The concept has permitted expanding breed- expressed sequence tags (EST) (3.3), but gene diversity between MEs ing efforts relevant within each ME. In breeding for was similar for both types of markers. No significant differences among enhanced adaptation, adequate genetic diversity is a the five MEs were observed for the means of SSR-based genetic prerequisite for any crop improvement program. The similarities (GS), calculated as 1 - Rogers’ distance, and COP values. Both measures showed a low correlation (r = 0.43). High levels of genetic progress through selection is directly related to genetic diversity were found within the germplasm targeted to each the variability present in the gene pool, and the quality ME. However, principle coordinate analysis based on modified Rog- of the genes contributed by the parents. ers’ distances did not separate the genotypes according to their tar- The COP is an indirect measure of genetic diversity geted MEs. We conclude that presence of a single core germplasm among genotypes based on the probability that alleles can reflect large phenotypic differences. A sufficient number of diverse at a certain locus are identical by descent. Calculation breeding lines for each ME is required because MEs generally com- of COP values rests on simplifying assumptions regard- bine various production areas. SSRs represent a powerful tool to ing the relatedness of ancestors, parental contribution quantify genetic diversity in wheat, but genotypic differentiation for to the offspring, and absence of selection and genetic adaptation to specific MEs in the CIMMYT program could not be drift, which are not met under breeding conditions (Cox proven. et al., 1985; Cowen and Frey, 1987). In contrast, molecu- lar markers measure diversity directly at the DNA level. In studies of autogamous crops with low levels of appar- W heat, together with maize (Zea mays L.) and rice ent genetic variability such as wheat, soybean [Glycine (Oryza sativa L.), is one of the three major food max (L.) Merr.], and rice, SSRs proved to be a suitable crops in the world. It is grown in a variety of environ- marker system. They are generally genome specific, ments, ranging from fully irrigated (e.g., northern India, abundant, codominant in nature, and show a fairly uni- Egypt), to high rainfall (e.g., northwestern Europe, east- form distribution over the genome. SSRs have been ern Africa, southern zone of Latin America), and applied in many aspects of genetic diversity analyses drought-prone regions (e.g., U.S. Great Plains, most of such as genetic differentiation caused by selection (Sta- Australia, parts of Argentina). In these areas wheat chel et al., 2000), fingerprinting of genotypes to analyze production experiences a range of biotic and abiotic the structure of germplasm collections (Parker et al., stresses and crop improvement requires precise focusing 2002; Huang et al., 2002), and the analysis of temporal on the needs of the crop in each area, the producers, changes in diversity (Donini et al., 2000; Christiansen the processing industry, and the consumers (Lantican et al., 2002). et al., 2002). Traditional methods to develop SSRs are based on More than one half of the wheat production environ- isolating and sequencing genomic libraries, which con- ments are located in developing countries, which fall within tain putative SSR tracts (Adams et al., 1992). A novel the mandate of CIMMYT. In the 1980s, CIMMYT intro- source for generating SSRs is provided by screening EST databases available online (Kota et al., 2001). This S. Dreisigacker and A.E. Melchinger, Inst. of Plant Breeding, Seed recent approach allows researchers to shift from the Science, and Population Genetics, Univ. of Hohenheim, 70593 Stutt- use of anonymous markers with unknown effect on the gart, Germany; M. Bohn, Dep. of Crop Science, Univ. of Illinois, phenotype to markers physically associated with coding Urbana, IL 61801; P. Zhang, M. van Ginkel, M.L. Warburton, and D. Hoisington, CIMMYT, Mexico D.F., Mexico. Received 17 March 2003. *Corresponding author (melchinger@pz.uni-hohenheim.de). Abbreviations: AMOVA, analysis of molecular variance; CIMMYT, International Maize and Wheat Improvement Center; COP, coeffi- Published in Crop Sci. 44:381–388 (2004).  Crop Science Society of America cient of parentage; EST, expressed sequence tag; GS, genetic similar- ity; ME, megaenvironment; SSR, simple sequence repeat. 677 S. Segoe Rd., Madison, WI 53711 USA 381