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Rebecca Nelson Brown and James R. Myers

., for providing seed of the parental lines, and greenhouse space for the development of the mapping population, and to H.S. Paris of Newe Ya'ar Research Station, Ramat Yishay, Israel, for fruitful discussion of the genetics of fruit color in Cucurbita .

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J. Erron Haggard and James R. Myers

White mold, caused by Sclerotinia sclerotiorum (Lib.) de Bary, causes major losses in dry and snap bean (Phaseolus vulgaris) production. With little genetic variation for white mold resistance in common bean, other potential sources for resistance must be investigated. Accessions of scarlet runner bean (P. coccineus) have been shown to have partial resistance exceeding any to be found in common bean. Resistance is quantitative with at least six QTL found in a P. coccineus intraspecific resistant × susceptible cross. Our goal is to transfer high levels of resistance from P. coccineus into commercially acceptable common bean lines. We developed interspecific advanced backcross populations for mapping and transfer of resistance QTL. 111 BC2F5 lines from a cross between OR91G and PI255956 have been tested in straw tests and oxalate tests, as well as in a field trial. The data show that the OR91G × PI255956 population carries a high level of resistance, but because of the quantitative nature of resistance, it may be necessary to intercross individuals to achieve higher levels. SSR, RAPD, and AFLP markers are being tested in the population to construct a linkage map for placement of QTL. QTL identified from each type of test (straw, oxalate, and field) may provide additional information about the genetic architecture of white mold resistance. Three other populations are from advanced backcrosses of the recurrent parents G122, OR91G, and MO162, with PI433251B as the donor parent in each. Analyses and advance of these populations will follow, the results of which should confirm QTL identified in the OR91G × PI255956 population, as well as possible additional resistance QTL from PI433251B.

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Melissa T. McClendon, Debra A. Inglis, Kevin E. McPhee, and Clarice J. Coyne

Dry pea (Pisum sativum L.) production in many areas of the world may be severely diminished by soil inhabiting pathogens such as Fusarium oxysporum f. sp. pisi race 1, the causal organism of fusarium wilt race 1. Our objective was to identify closely linked marker(s) to the fusarium wilt race 1 resistance gene (Fw) that could be used for marker assisted selection in applied pea breeding programs. Eighty recombinant inbred lines (RILs) from the cross of Green Arrow (resistant) and PI 179449 (susceptible) were developed through single-seed descent, and screened for disease reaction in race 1 infested field soil and the greenhouse using single-isolate inoculum. The RILs segregated 38 resistant and 42 susceptible fitting the expected 1:1 segregation ratio for a single dominant gene (χ2 = 0.200). Bulk segregant analysis (BSA) was used to screen 64 amplified fragment length polymorphism (AFLP) primer pairs and previously mapped random amplified polymorphic DNA (RAPD) primers to identify candidate markers. Eight AFLP primer pairs and 15 RAPD primers were used to screen the RIL mapping population and generate a linkage map. One AFLP marker, ACG:CAT_222, was within 1.4 cM of the Fw gene. Two other markers, AFLP marker ACC:CTG_159 at 2.6 cM linked to the susceptible allele, and RAPD marker Y15_1050 at 4.6 cM linked to the resistant allele, were also identified. The probability of correctly identifying resistant lines to fusarium wilt race 1, with DNA marker ACG:CAT_222, is 96% percent. These markers will be useful for marker assisted breeding in applied pea breeding programs.

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Phillip N. Miklas, Richard Delorme, and Ron Riley

Host resistance is an important component of integrated disease management strategies for control of Sclerotinia white mold disease in snap bean (Phaseolus vulgaris L.). Few resistant snap bean cultivars have been bred, however, because genetic resistance to white mold is not well understood. This study was conducted to examine inheritance and identify quantitative trait loci (QTL) for white mold resistance in an F5:7 recombinant inbred line (RIL) population (`Benton'/NY6020-4). `Benton' snap bean is susceptible to white mold. Snap bean germplasm line NY6020-4 has partial resistance. The parents and 77 F5:7 RILs were tested for resistance to white mold across four greenhouse and two field environments. Moderately high heritability estimates were observed for straw test (0.73) and field (0.62) reaction. Selective mapping of 27 random amplified polymorphic DNA (RAPD) markers detected two QTL conditioning resistance to white mold on linkage groups B6 and B8 of the core map. The B6 QTL explained 12% and B8 QTL 38% of the variation for disease reaction in the straw test. The two QTL explained 13% and 26% disease reaction in the field, respectively. Favorable alleles for all the QTL were derived from NY6020-4, except for the B6 QTL conditioning resistance to white mold in the field, which was derived from `Benton'. The B6 QTL was located near the Ur-4 rust resistance gene, and was associated with canopy height and lodging traits that condition disease avoidance. The B8 QTL was associated with increased internode length, an undesirable trait in snap bean, which may hamper use of white mold resistance derived from NY6020-4.

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Riaz Ahmad, Darush Struss, and Stephen M. Southwick

We evaluated the potential of microsatellite markers for use in Citrus genome analysis. Microsatellite loci were identified by screening enriched and nonenriched libraries developed from `Washington Navel' Citrus. Microsatellite-containing clones were sequenced and 26 specific PCR primers were selected for cross-species amplification and identification of cultivars/clones in Citrus. After an enrichment procedure, on average 69.9% of clones contained dinucleotide repeats (CA)n and (CT)n, in contrast to <25% of the clones that were identified as positive in hybridization screening of a nonenriched library. A library enriched for trinucleotide (CTT)n contained <15% of the clones with (CTT)n repeats. Repeat length for most of the dinucleotide microsatellites was in the range of 10 to 30 units. We observed that enrichment procedure pulled out more of the (CA)n repeats than (CT)n repeats from the Citrus genome. All microsatellites were polymorphic except one. No correlation was observed between the number of alleles and the number of microsatellite repeats. In total, 118 putative alleles were detected using 26 primer pairs. The number of putative alleles per primer pair ranged from one to nine with an average of 4.5. Microsatellite markers discriminated sweet oranges [Citrus sinensis (L.) osb], mandarin (Citrus reticulata Blanco), grapefruit (Citrus paradisi Macf.), lemon [Citrus limon (L.) Burm.f.], and citrange (hybrids of trifoliate orange and sweet orange), at the species level, but individual cultivars/clones within sweet oranges, mandarins and grapefruit known to have evolved by somatic mutation remained undistinguishable. Since these microsatellite markers were conserved within different Citrus species, they could be used for linkage mapping, evolutionary and taxonomic study in Citrus.

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James W. Olmstead, Hilda Patricia Rodríguez Armenta, and Paul M. Lyrene

Because of financial and labor concerns, growers are interested in using machine harvesting for fruit destined to be fresh marketed. Machine harvest of highbush blueberry (Vaccinium corymbosum) has typically been used to obtain large volumes of fruit destined for processing. Bush architecture, easy detachment of mature berries compared with immature berries, loose fruit clusters, small stem scar, firm fruit, and a concentrated ripening period are breeding goals to develop cultivars amenable to machine harvest. In the University of Florida (UF) southern highbush blueberry [SHB (Vaccinium corymbosum hybrids)] breeding program, sparkleberry (Vaccinium arboreum) has been used in wide crosses in an attempt to introgress traits that may be valuable for machine harvesting, namely upright growth habit with a narrow crown and long flower and fruit pedicels creating loose fruit clusters. Two eras of sparkleberry hybridization experiments have occurred since the early 1980s. The first era used darrow’s evergreen blueberry (Vaccinium darrowii) as a bridge between sparkleberry and tetraploid SHB, with the recently released cultivar FL 01-173 (sold under the trademarked name Meadowlark) as an example of the end product. The second era has used chromosome doubling to develop polyploid sparkleberry selections that were directly crossed with tetraploid SHB. After 1 year of evaluation, a SHB × (SHB × sparkleberry) population developed for linkage and quantitative trait locus mapping showed abundant variation for length:width ratio of the plant, but similarity to the highbush phenotype for peduncle and pedicel length of the fruit. These first evaluations indicate evidence of introgression and provide an initial step toward improved cultivars for mechanical harvesting.

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Allan F. Brown, Elizabeth H. Jeffery, and John A. Juvik

using the Kosambi mapping function of the JOINMAP program ( van Ooijen and Voorrips, 2001 ). An independence logarithm of odds (LOD) score of 3.0 was required for grouping of the markers and the order of the markers on each linkage group was determined

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Amnon Levi and Claude E. Thomas

has been a challenging task to develop codominant SSR markers in watermelon as has been indicated in our recent mapping study ( Levi et al., 2006 ). The assembly of markers from different linkage regions of the watermelon genome is vital in

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Soon O. Park, Dermot P. Coyne, Geunhwa Jung, Paul W. Skroch, E. Arnaud-Santana, James R. Steadman, H.M. Ariyarathne, and James Nienhuis

Our objective was to identify quantitative trait loci (QTL) for seed weight, length, and height segregating in a recombinant inbred line population derived from the common bean (Phaseolus vulgaris L.) cross `PC-50' × XAN-159. The parents and progeny were grown in two separate greenhouse experiments in Nebraska, and in field plots in the Dominican Republic and Wisconsin. Data analysis was done for individual environments separately and on the mean over all environments. A simple linear regression analysis of all data indicated that most QTL appeared to be detected in the mean environment. Based on these results, composite interval mapping (CIM) analysis was applied to the means over environments. For seed weight, strong evidence was indicated for five QTL on common bean linkage groups (LGs) 3, 4, 6, 7, and 8. Multiple regression analysis (MRA) indicated that these QTL explained 44% of the phenotypic variation for the trait. Weaker evidence was found for three additional candidate QTL on bean LGs 4, 5, and 8. All eight markers associated with these QTL were significant in a MRA where the full model explained 63% of the variation among seed weight means. For seed length, CIM results indicated strong evidence for three QTL on LG 8 and one on LG 2. Three additional putative QTL were detected on LGs 3, 4, and 11. The markers associated with the three seed length QTL on LG 8, and the QTL on LGs 2 and 11 were significant in a MRA with the full model explaining 48% of the variation among seed length means. For seed height, three QTL on LGs 4, 6, and 11 explained 36% of the phenotypic variation for trait means. Four of the seven QTL for seed length and two of three QTL for seed height also appeared to correspond to QTL for seed weight. Four QTL for common bacterial blight resistance [Xanthomonas campestris pv. phaseoli (Smith Dye)] and for smaller seed size were associated on LGs 6, 7, and 8. The implications of these findings for breeders is discussed.

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Darush Struss, Riaz Ahmad, Stephen M. Southwick, and Manuela Boritzki

Simple sequence repeats (SSRs) and amplified fragment-length polymorphisms (AFLPs) were used to evaluate sweet cherry (Prunus avium L.) cultivars using quality DNA extracted from fruit flesh and leaves. SSR markers were developed from a phage library using genomic DNA of the sweet cherry cultivar Valerij Tschkalov. Microsatellite containing clones were sequenced and 15 specific PCR primers were selected for identification of cultivars in sweet cherry and for cross-species amplification in Prunus. In total, 48 alleles were detected by 15 SSR primer pairs, with an average of 3.2 putative alleles per primer combination. The number of putative alleles ranged from one to five in the tested cherry cultivars. Forty polymorphic fragments were scored in the tested cherry cultivars by 15 SSRs. All sweet cherry cultivars were identified by SSRs from their unique fingerprints. We also demonstrated that the technique of using DNA from fruit flesh for analysis can be used to maintain product purity in the market place by comparing DNA fingerprints from 12 samples of `Bing' fruit collected from different grocery stores in the United States to that of a standard `Bing' cultivar. Results indicated that, with one exception, all `Bing'samples were similar to the standard. Amplification of more than 80% of the sweet cherry primer pairs in plum (P. salicina), apricot (P. armeniaca) and peach (P. persica L.) showed a congeneric relationship within Prunus species. A total of 63 (21%) polymorphic fragments were recorded in 15 sweet cherry cultivars using four EcoRI-MseI AFLP primer combinations. AFLP markers generated unique fingerprints for all sweet cherry cultivars. SSRs and AFLP polymorphic fragments were used to calculate a similarity matrix and to perform UPGMA cluster analysis. Most of the cultivars were grouped according to their pedigree. The SSR and AFLP molecular markers can be used for the grouping and identification of sweet cherry cultivars as a complement to pomological studies. The new SSRs developed here could be used in cherry as well as in other Prunus species for linkage mapping, evolutionary and taxonomic study.