Appropriate selection of parents for the development of mapping populations is pivotal to maximizing the power of quantitative trait loci detection. Trait genotypic variation within a family is indicative of the family's informativeness for genetic studies. Accurate prediction of the most useful parental combinations within a species would help guide quantitative genetics studies. We tested the reliability of genotypic and phenotypic distance estimators between pairs of maize inbred lines to predict genotypic variation for quantitative traits within families derived from biparental crosses. We developed 25 families composed of B200 random recombinant inbred lines each from crosses between a common reference parent inbred, B73, and 25 diverse maize inbreds. Parents and families were evaluated for 19 quantitative traits across up to 11 environments. Genetic distances (GDs) among parents were estimated with 44 simple sequence repeat and 2303 single-nucleotide polymorphism markers. GDs among parents had no predictive value for progeny variation, which is most likely due to the choice of neutral markers. In contrast, we observed for about half of the traits measured a positive correlation between phenotypic parental distances and within-family genetic variance estimates. Consequently, the choice of promising segregating populations can be based on selecting phenotypically diverse parents. These results are congruent with models of genetic architecture that posit numerous genes affecting quantitative traits, each segregating for allelic series, with dispersal of allelic effects across diverse genetic material. This architecture, common to many quantitative traits in maize, limits the predictive value of parental genotypic or phenotypic values on progeny variance.

Teosinte (Zea mays subsp. parviglumis H. H. Iltis & Doebley) has greater genetic diversity than maize inbreds and landraces (Z. mays subsp. mays). There are, however, limited genetic resources to efficiently evaluate and tap this diversity. To broaden resources for genetic diversity studies in maize, we developed and evaluated 928 near-isogenic introgression lines (NILs) from 10 teosinte accessions in the B73 background. Joint linkage analysis of the 10 introgression populations identified several large-effect quantitative trait loci (QTL) for days to anthesis (DTA), kernel row number (KRN), and 50-kernel weight (Wt50k). Our results confirm prior reports of kernel domestication loci and identify previously uncharacterized QTL with a range of allelic effects enabling future research into the genetic basis of these traits. Additionally, we used a targeted set of NILs to validate the effects of a KRN QTL located on chromosome 2. These introgression populations offer novel tools for QTL discovery and validation as well as a platform for initiating fine mapping.

Microsatellite or simple sequence repeat (SSR) markers have wide applicability for genetic analysis in crop plant improvement strategies. The objectives of this project were to isolate, characterize, and map a comprehensive set of SSR markers for maize (Zea mays L.). We developed 1051 novel SSR markers for maize from microsatellite-enriched libraries and by identification of microsatellite-containing sequences in public and private databases. Three mapping populations were used to derive map positions for 978 of these markers. The main mapping population was the intermated B73 x Mo17 (IBM) population. In mapping this intermated recombinant inbred line population, we have contributed to development of a new high-resolution map resource for maize. The primer sequences, original sequence sources, data on polymorphisms across 11 inbred lines, and map positions have been integrated with information on other public SSR markers and released through MaizeDB at URL:www.agron.missouri.edu. The maize research community now has the most detailed and comprehensive SSR marker set of any plant species.

A map derived from restriction fragment length polymorphisms (RFLPs) in maize (Zea mays L.) is presented. The map was constructed in an immortalized Tx303 x CO159 F2 mapping population that allowed for an unlimited number of markers to be mapped and pooled F3 seed to be distributed to other laboratories. A total of 215 markers consisting of 159 genomic clones, 16 isozymes and 35 cloned genes of defined function have been placed on 10 chromosomes. An examination of segregation data has revealed several genomic regions with aberrant segregation ratios favoring either parent or the heterozygote. Mapping of cloned genes and isozymes that have been previously mapped by functional criteria has provided 29 points of alignment with the classical maize genetic map. Screening of all mapped RFLP probes against a collection of U.S. Corn Belt germplasm using EcoRI, HindIII and EcoRV has resulted in a set of 97 core markers being defined. The designation of a set of core markers allows the maize genome to be subdivided into a series of bins which serve as the backbone for maize genetic information and database boundaries. The merits and applications of core markers and bins are discussed.

We have constructed a 1736-locus maize genome map containing1156 loci probed by cDNAs, 545 probed by random genomic clones, 16 by simple sequence repeats (SSRs), 14 by isozymes, and 5 by anonymous clones. Sequence information is available for 56% of the loci with 66% of the sequenced loci assigned functions. A total of 596 new ESTs were mapped from a B73 library of 5-wk-old shoots. The map contains 237 loci probed by barley, oat, wheat, rice, or tripsacum clones, which serve as grass genome reference points in comparisons between maize and other grass maps. Ninety core markers selected for low copy number, high polymorphism, and even spacing along the chromosome delineate the 100 bins on the map. The average bin size is 17 cM. Use of bin assignments enables comparison among different maize mapping populations and experiments including those involving cytogenetic stocks, mutants, or quantitative trait loci. Integration of nonmaize markers in the map extends the resources available for gene discovery beyond the boundaries of maize mapping information into the expanse of map, sequence, and phenotype information from other grass species. This map provides a foundation for numerous basic and applied investigations including studies of gene organization, gene and genome evolution, targeted cloning, and dissection of complex traits.