Mapping and QTL Analysis of Plant Architecture and Fruit Yield In

160 Chapter III

Mapping and QTL Analysis of Plant Architecture and Fruit Yield in

Melon (Cucumis melo L.)

Abstract

The inheritance of plant architecture and fruit yield (hereafter designated yield component) in melon (Cucumis melo L.; 2n = 2x = 24) is poorly understood, and the mapping of quantitative trait loci (QTL) for yield components has not been reported. Unique highly branched melon types may have potential for increasing yield. Genetic mapping of yield components using such unique phenotypes is critical for gaining an understanding of the complex source-sink relations affecting yield components. Therefore, a set of 81 recombinant inbred lines (RIL) was developed from a cross between a monoecious, highly branched, line, U. S. Department of Agriculture (USDA) 846-1 (P1) and a standard vining, andromonoecious cultivar, “Top Mark” (P2). The RIL, parental lines, and three control cultivars (“Esteem”, “Sol Dorado”, and “Hales Best Jumbo”) were grown at Hancock,

Wisconsin and El Centro, California in 2002, and sex expression (ESX), primary branch number (PB), fruit number per plant (FN), fruit weight per plant (FW), average weight per fruit (AWF), and percentage of mature fruit per plot (PMF) data were collected. A 181-point genetic map was constructed using 114 RAPD, 35 SSR, and 32 AFLP markers. Fifteen linkage groups spanned 1,032 cM with a mean marker interval of 5.7 cM. A total of 38 QTL were detected in both locations (EXS = 4, PB = 7, FN = 10, FW = 9, AWF = 5, and PMF =

3). QTL analyses of EXS identified three environmentally-dependent QTL (exs4.1, exs6.2, and exs9.4), and one environmentally-independent QTL (exs8.3) on linkage Group 8, which 161 likely corresponds to the a locus (controlling pistillate/hermaphroditic flowering). Similarly,

QTL analyses revealed four location-independent factors for PB (pb1.1, pb1.2, pb2.3, and pb10.5), three for FN (fn1.1, fn1.3, and fn5.6), four for FW (fw1.1, fw5.6, fw6.7, and fw8.8), and two for AWF (awf1.2 and awf4.3). Two-dimensional genome scans revealed numerous epistatic interactions for FW, AWF, and PMF, which indicate that additional genomic regions operate to control these traits. The data presented herein indicate that efficient conventional phenotypic selection coupled with marker-assisted selection will result in the development of monoecious, highly branched germplasm with concentrated fruit set suited for once-over or mechanical operations.

Key words: Exotic germplasm, primary branch number, best linear unbiased predictions (BLUPs), best linear unbiased estimations (BLUEs), linkage analysis, composite interval mapping, quantitative trait loci.

Introduction

Most traits of economic importance such as yield are polygenetic, and thus their inheritance is complex (Lande and Thompson, 1990). In general, selection for yield has been difficult, and has relied on the estimation of genetic parameters (e.g., variance components, heritabilities, and least number of effective factors) for the strategic planning and allocation of resources (i.e., choice of selection method and extent of evaluation over locations and years) (Comstock, 1978; Dudley and Moll, 1969; Falconer and Mackay, 1996; Hallauer and

Miranda, 1988; Lande, 1981). Such parameters have traditionally been estimated using complex statistically-based biometrical methods such as North Carolina Designs (Comstock 162 and Robinson, 1948, 1952), diallel analysis (Eberhart and Gardner, 1966; Gardner and

Eberhart, 1966; Griffing, 1956), and variance component analysis employing inbred progenies (Mather, 1949; Mather and Jinks, 1971). These methodologies, however, aim to estimate the average properties of genes or quantitative trait loci (QTL), but dot not allow for the dissection and quantification of individual genetic effects (Kearsey and Pooni, 1998;

Lynch and Walsh 1998).

QTL analysis provides an opportunity for the genetic dissection of economically important traits (Fulton et al., 1997; Galmarini et al., 2001; Krakowsky et al., 2003; Marquez-Cedillo et al., 2000; Santos and Simon, 2002; Septiningsih et al., 2003; Quijada et al., 2004). In melon

(Cucumis melo L; 2n = 2x =24), only Cucumber Mosaic Virus resistance (CMV) (Dogimont et al., 2000), ethylene production during fruit maturation (Perin et al., 2002a), and several melon fruit quality traits have been the focus of QTL analysis (Monforte et al., 2004; Perin et al., 2002b). The scarcity of QTL mapping studies in melon is due to the fact that most linkage maps in this crop species have been developed using F2 and BC1 populations that are not adequate for extensive QTL analysis (Baudracco-Arnas and Pitrat 1996; Danin-Poleg et al. 2002; Liou et al., 1998; Oliver et al., 2001; Silberstein et al. 2003; Wang et al., 1998).

Moreover, until recently, maps developed from immortalized melon populations such as recombinant inbred lines (RIL) (Périn et al., 2002a, 2002b, 2002c) and double haploid lines

(DHL) (Gonzalo et al., 2005) were not available.

Few studies have investigated the genetics of plant architecture (e.g., primary branch number) and fruit yield (e.g., fruit number and weight per plant; Lippert and Legg, 1972; 163 Lippert and Hall, 1982) in melon (hereafter referred as yield components), and QTL analysis has not been performed for such traits. The inheritance of yield components was investigated using generation means analysis (Chapter I) and variance components analysis (Chapter II).

A combination of additive, dominance, epsitatic effects, as well as genotype x environment interactions (G x E) were detected for most of the yield-associated traits examined. While four factors were estimated to control the inheritance of primary branch number, dominance, epistasis, and G x E interactions made calculations difficult for the other traits examined

(Chapters I and II). If the predictive value of QTL controlling these traits could be defined, then the efficiency of plant selection for improved yield in melon might be enhanced by marker-assisted selection (MAS). Thus, a study was designed to create a molecular map in melon for the identification and localization of QTL associated with yield components. This study employed a relatively wide cross between a line possessing a unique multiple branching growth habit and a standard vining Western Shipping type line to produce an array of RIL as a first step in the development of high yielding germplasm with early concentrated fruit set.

Materials and Methods

PLANT MATERIAL. A horticulturally unique germplasm designated CR1 (received in 1995 from Mr. Claude Hope, Cartago, Costa Rica), which is characterized by its extreme “fractal” or radiant growth habit (Mandelbrot, 1983; Prusinkiewicz and Haran, 1989; Prusinkiewicz and Lindenmayer, 1990; Smith, 1984), is available from the U.S. Department of Agriculture,

Agricultural Research Service (USDA, ARS) melon breeding project, Madison, Wisconsin 164 (Appendix 1). This accession, C. melo ssp. agrestis (Naud.) Pangalo, is early flowering, monoecious, fast growing, indeterminate, possesses standard size internodes, abundant branching (6 to 12 primary branches), and bears many small fruits (up to 100 fruits/plant) 3 to 6 cm in diameter (Staub et al., 2004; Zalapa et al., 2004). The fractal architecture of CR1 is unique and distinct from vining (Rosa, 1924), dwarf (Denna, 1962; Mohr and Knavel,

1966), and birdnest (Paris et al., 1981, 1982, 1984) plant habits (Figure 3, Introduction).

A monoecious, early flowering CR1 plant having 12 primary branches was crossed to an F1 plant derived from a cross between USDA line FMR#8 x line SC#6 (Chapter 1). A monoecious, early flowering plant from this mating was selected and self-pollinated four times to produce an S3 inbred line designated USDA 846-1 (Appendixes 2 to 4; Staub et al.,

2004; Zalapa et al., 2004). The monoecious, highly branched fractal USDA 846-1 (P1) line was crossed to “Top Mark” (P2), which is andromonoecious, possesses between two to four lateral branches, and produces a diffuse, distal fruiting setting habit typical of vining melon types (Appendixes 2 to 4, Staub et al., 2004; Zalapa et al., 2004). A single F1 plant from this initial mating was self-pollinated to generate F2 individuals, which were subsequently used in a single-seed descent procedure to produce an array 81 RIL (F6; Appendix III-1).

EXPERIMENTAL DESIGN. The two parental lines, 81 RIL, and three commercial cultivars,

“Esteem” (ES) and “Sol Dorado” (SD) (Syngenta Seeds, Gilroy, Calif.), and “Hales Best

Jumbo” (HB) (Excel Seeds, Chattanooga, Tenn.) were evaluated at the University of

Wisconsin experimental farm at Hancock, Wisconsin and at the University of California

Desert Research and Extension Center, Meloland Station, El Centro, California. The 165 experimental design at both locations was a randomized complete block design (RCBD) consisting of four blocks with 10 plants per plot. “Esteem”, “Sol Dorado”, and “Hales Best

Jumbo” were used as controls to provide a benchmark for yield component and maturation rate comparisons.

For the experiment conducted in Wisconsin, seeds from all entries were sown in 72-unit plastic potting trays (T. O. Plastics, Inc., Clearwater, MN) containing Growing Mix No. 2

(Conrad Fafard, Inc., Agawam, MA). Trays were held in a greenhouse at UW Madison,

Wisconsin during the spring of 2002, watered once a day, and fertilized (N:P:K = 20:20:20) twice before transplanting. Three-week old seedlings were “hardened-off” for three days, fertilized with starter fertilizer (N:P:K = 10:24:8), and then transplanted every 0.35 m within rows on 2 m centers (72,600 plants/ha) at Hancock, WI (average season temperature, May –

August = 60 °F and average relative humidity = 68%). Standard cultivation practices were followed according to UWEX (2001) for Hancock’s Planefield loamy sand (Typic

Udipsamment) soil. In the Fall of 2002, 12 seeds of each entry were sown singly in a field in

El Centro, California (Imperial silty clay Vertic Torrifluvents; average season temperature,

August - November = 79 °F and average relative humidity = 36%) on raised beds every 0.35 m within rows on 2 m centers. At the two-leaf stage, each plot was thinned to 10 plants per plot. Water and fertilizer were delivered through a drip line irrigation system following cultural practices for commercial melon production in the Imperial Valley growing region.

DATA COLLECTION. Sex expression (EXS) was recorded in Wisconsin at 30 (EXS-W30),

45 (EXS-W45), and 60 (EXS-W60) days after transplant, and in California 45 (EXS-C45) 166 days after sowing. Sex expression in an experimental plot was characterized as: 1) H = plot contained only hermaphrodite and staminate flowers; 2) H/M = plot contained hermaphrodite, pistillate, and staminate flowers, and; 3) M = plot contained only pistillate and staminate flowers. The number of primary branches (PB) for each plant was counted 30 days after transplant in Wisconsin, and 45 days after sowing in California to include all branches of more than 12.5 cm in length below the fourth node. Fruit number (FN) and fruit weight (FW; kg) data (fruit at least 7.5 cm in diameter) were collected per plant 80 days after transplanting in Wisconsin and 90 days after sowing in California. The average weight per fruit (AWF; kg) was calculated for each plant by dividing the total number of fruit per plant by the total weight per plant. The percentage of mature fruit (PMF) per plot was calculated by dividing the number of mature fruit in a plot (fruit assessed by their fruit scar, color, aroma, netting, and flesh color) at the time of harvest (80 days after transplant in Wisconsin and 90 days after sowing in California) by the total number of fruit in that plot.

ANALYSIS OF VARIANCE. Histograms were created using the statistical package “R” (R

Development Core Team, 2003) to assess the normality of the phenotypic distributions of the

RIL (Appendix III-2 and III-3). Location data were initially combined to perform analyses of variance (ANOVA) using the proc mixed covtest method type3 procedure of SAS (SAS,

1999) (Appendix III-4). Additionally, variance components were estimated employing restricted maximum likelihood (REML), and each variance estimate was tested for significance using the likelihood ratio statistic (Littell, 1996). The linear random-effects

model for such analyses was the following: Y =  + L + B(L) + F + L x F + e; where Y is the trait (i.e., PB, FN, FW, AWF, PCF, and PMF),  is the common effect, L is the location 167 effect, B(L) is the block within location effect, F is the effect of the RIL, L x F is the location x RIL interaction effect, and e is the plot-to-plot variation within the RIL (Appendix III-4).

Analyses of the RIL were also performed by location for all traits.

Best linear unbiased predictions (BLUPs) have been used for QTL analysis in several plant species (Borevitz et al., 2002; Bernardo, 1998; Jones et. al., 2002; de Leon et al., 2005).

BLUPs, standard errors, (S.E.), confidence intervals (95%) (C.I.s), and tBLUPs were estimated as described in Chapter II. The two parental inbred lines (P1 and P2) and the control cultivars (i.e., ES, SD, and HB) were analyzed independently using a linear mixed- effects model. The parental lines and control cultivars were considered as fixed effects, and best linear unbiased estimations (BLUEs) were estimated according to Chapter II. The 95%

C.I.s of RIL BLUPs and the BLUEs of the parental lines and control cultivars were used for comparisons of genotype performance. When the BLUE of the parental lines and/or control cultivars lied outside the C.I. limit of the BLUP of the RIL, such genotypes were considered to be significantly (p ≤ 0.05) different from each other (de Leon et al., 2005).

In order to assess whether G x E interactions were due to trait magnitude changes between locations or changes in the direction of the response (i.e., RIL rank changes), Spearman

(rank) correlation coefficients (rs; Johnson, 1996) were calculated using the tBLUPs (Yan and Rajcan, 2003) values of the RIL for each individual trait between locations (Chapter II).

When the correlation coefficient between tBLUPs across locations was rs ≤ 0.5, G x E interactions were considered more likely to be due to RIL rank changes, whereas when rs ≥ 168 0.5, G x E interactions were considered more likely to be due to trait magnitude changes between locations (Chapter II).

PHENOTYPIC CORRELATIONS. Phenotypic correlations (r; n =81) between pairs of traits were calculated by location using the proc corr spearman procedure of SAS (SAS 1999).

ESTIMATION OF HERITABILITIES. The broad-sense heritabilities based on RIL BLUPs

2 2 2 2 2 2 (h BF) were calculated as h BF = ( F)/ PF; where  F and  PF are the variance among RIL and

2 phenotypic variance based on RIL BLUPs, respectively. The estimate of  PF was calculated

2 2 2 2 2 2 as  F +  LxF/b +  e/bl; where b, l,  F,  LxF and  e refer to the number of blocks, the number of locations, the variance among RIL, the variance due to location x RIL interactions, and the plot-to-plot variation within RIL, respectively (Falconer and Mackay, 1996). The standard

2 error of broad-sense heritabilities based on RIL BLUPs were calculated as S.E.(h BF) =

2 1/2 2 [Var( F)] / PF .

DNA EXTRACTION. Young leaves and apical meristems of at least 10 plants of each of the

81 RIL, the parental lines, and their F1 hybrid were bulk sampled, and each sample was vacuum dried and grounded into a fine powder. Genomic DNA was isolated using approximately 0.15 g of grounded leaf tissue of each sample, which was mixed with 600 μl of 1X Lysis buffer (5% SDS, 0.1M EDTA), vortexed for 30 s, and incubated in a 65ºC water bath for 1.5 h. After cooling to room temperature, 200 μl of 5M ammonium acetate were added to each sample, which were subsequently vortexed for 20 s and centrifuged for 10 min at 14, 000 xg. The supernatants were then transferred into 2.0 ml tubes, and 600 μl of 100% 169 isopropanol were added and mixed by gentle inversion. Solutions were centrifuged at 14,000 xg for 10 min, and the resulting pellets were subsequently rinsed with 600μl 75% ethanol, allowed to air-dry, and then re-suspended in 200μl TE buffer (10mM Tris, 1mM EDTA, PH

8.0). Extraction products were treated with “RNAse ONE” as described by the manufacturer

(Promega, Madison, WI), and the concentration (ng of DNA/μl) of the genomic DNA was determined by electrophoresis on 1.0% agarose gels using calf thymus DNA as the standard, after which DNA samples were stored at –20ºC.

RANDOM AMPLIFIED POLYMORPHIC DNA (RAPD) ANALYSIS. A set of primers found to be polymorphic in diverse melon accessions (Staub, 2001) were used to assay the RIL population (Appendix III-16). Primers (10-mer) were obtained from Operon Technologies,

Alameda, CA (OP) and the University of British Columbia, Vancouver, Canada (BC). All

PCR solutions were purchased from Promega (Madison, WI). Each PCR reaction was performed using a 15μl volume and contained 1.5μl 10X PCR buffer, 2.43μl 25mM MgCl2,

3.24μl dNTPs (1.25mM of each dATP, dGTP, dTTP, and dCTP), 1.35μl 5μM primer, 5μl

3ng/μl genomic DNA, 1 u Taq DNA polymerase, and 1.44μl H2O. Thermocycling conditions were as follows: An initial melting step (94˚C for 3 min), then 50 cycles (94˚C for

15 s, 36˚C for 90 s, and 72˚C for 2 min), a final elongation step (72˚C for 6 min), and then an indefinite soak at 4˚C.

After completion of the PCR, 5μl of loading dye were added to each reaction. The samples were electrophoresed using 1.6% agarose gels containing 0.5μg/ml ethidium bromide in 0.5X

TBE buffer (6.055% Tris Base, 0.3725% EDTA, 2.85% Boric acid) for 3.5 h at 180 v using 170 OWL separation systems (Portsmouth, NH). Gels were visualized with a Dark ReaderTM transilluminator (Clare Chemical Inc., Denver, CO), and photographed using a closed circuit digital (CCD) camera. Only bright and consistent bands of 2.2kb or less were scored, and

DNA fragment sizes were estimated by comparative analysis with EcoRI and HindIII digested Lambda DNA band migrations. Each band was designated by the abbreviated company name, the name of RAPD primer plus the fragment size of PCR product (e.g.,

OPAR1-700). RAPD markers were scored as codominant markers if the parental lines and

F1 hybrid showed codominant segregation patterns, and a RIL with both bands absent (null) was never observed.

SINGLE SEQUENCE REPEATS (SSR) ANALYSIS. SSR markers from different sources (Danin-

Poleg et al., 2001; Fazio et al., 2002; Gonzalo et al., 2005; Katzir et al., 1996) were evaluated for their potential value in map construction using the RIL population (Appendix III-16).

SSR PCR reaction preparation was the same as for RAPD analysis. Thermocycling conditions were previously described by Danin-Poleg et al. (2001), Fazio et al. (2002),

Gonzalo et al. (2005), and Katzir et al. (1996). Marker data analysis were performed both by gel electrophoresis (on 3.5% agarose gels) and at the University of Wisconsin Biotechnology

Center DNA Sequence Facility using a Applied Biosystems 3700 fluorescent sequencer

(POP-6 and a 50 cm array) and the Gene Scan Analysis Software version 3.1 of Applied

Biosystems (Foster City, CA). If single sequence repeat (SSR) markers proved to have the predicted base pair length, they were labeled according to the marker designations given by the initial reference source. If SSRs revealed a dominant segregation pattern in both gel electrophoresis and GeneScan analyses, they were scored as dominant markers, and 171 designated (Do) plus the name of the original SSR primer pair combinations and the base pairs fragment size (e.g., DoTJ10-120).

AMPLIFIED FRAGMENT LENGTH POLYMORPHIM (AFLP) ANALYSIS. Protocol of AFLP was according to the methodologies described by Vos et al. (1995) and the AFLP protocol of

Berres (http://ravel.zoology.wisc.edu/sgaap/AFLP_html/AFLP.htm) with the modifications described by Sun (2004) (Appendix III-16). AFLP markers were designated as specified by

Vos et al. (1995), where designations were derived from the restriction enzymes used to produce the DNA fragments (i.e., EcoRI and MseI), their specific primer combinations, and the size of the polymorphic band given in base pairs (e.g., E19M47-74).

LINKAGE MAP CONSTRUCTION. Dominant marker bands were scored as 1 (present) or 0

(absent), while codominant bands were scored as 0 and 1 for the homozygous parent P1 and the homozygous parent P2, respectively. Segregation ratio distortion tests were performed in

JoinMap 3.0 (Van Ooijen and Voorrips, 2001) as assessments of predicted dominant and codominant marker ratios (1:1 for RIL) (Appendix III-16). Markers with chi-square p-values greater than 0.01 were employed for linkage analysis (Marques et al., 1998; Vuylsteke et al.,

1999) using MapMaker/EXP 3.0 (Lander et al. 1987). Markers were assigned to linkage groups using LOD and recombination frequency threshold values of 3.5 and 0.35, respectively (Appendix III-16). The recombination fraction frequencies were converted to map distances using the Kosambi mapping function by employing the centiMorgan function command, and the three point command was utilized for multi-point analysis. For each linkage group, the order command with five specified parameters was used to choose a seed 172 order (order with the highest log-likelihood ratio) of highly informative markers. Since the order command may identify different markers for a seed order during each iteration, this step was performed at least five times to choose the best seed order, and then the remaining markers from each linkage group were manually added sequentially to the seed order using the try command. During each iteration, a marker with the most likely position was placed, and the map order was re-tested using the ‘ripple’ command at a LOD 2.0.

QTL MAPPING. Composite interval mapping (Zeng, 1993; Zeng, 1994) was performed for all traits using Windows QTL Cartographer 2.0 (Wang et al., 2001-2004) (Appendixes III-17 to III-33). A stepwise forward regression procedure employing a walking speed of 1 cM, a window size of 5 cM, and the inclusion of 10 maximum background marker loci was used to eliminate background effects inherent among linked multiple QTL. For sex expression data, a non-parametric model using the Kruskal-Wallis test (NP) (Kruklyak and Lander, 1995) was also performed in R/qtl (Broman et al., 2003) (Appendixes III-17). In the NP model, average ranks were used to identify ties among observed phenotypes by setting ties.random =

FALSE. The multi-point genotype probabilities were calculated by Haley Knott (HK) regression analysis using the calc.genoprob command with the step interval of step = 2 cM and error probability of error.prob = 0.01.

TWO-DIMENSIONAL EPISTASIS GENOME SCANS. Two-dimensional genome scans for detection of epistatic interactions were performed in R/qtl (Broman et al., 2003) by employing the Haley-Knott regression (HK) (Haley and Knott, 1992; Appendixes III-34 to

III-45). The multi-point genotype probabilities for the HK regression analyses used in the 173 two-QTL model were calculated using the calc.genoprob command with a step interval of step = 2 cM and an error probability of error.prob = 0.01.

LOD THRESHOLDS. A QTL was declared significant when its LOD score was higher than the LOD threshold calculated using 1000 permutations (Churchill and Doerge, 1994) for an experimental-wise (type I) error rate of p = 0.05 or when, in at least two locations, the LOD was higher than 2.5, except for the LOD threshold of sex expression which was set at 3.0.

The LOD thresholds for the two-QTL model analysis were determined by 1000 permutations, which represents the range of the 95% quartile of 1000 permutations.

Results

ANALYSIS OF VARIANCE. The RIL used in this study were phenotypically diverse in plant habit, fruit development, and maturity characteristics (Appendixes 4). All phenotypic distributions were normally distributed, except for sex expression (Appendixes III-2 to III-3).

Thus, analysis of variance was not performed for sex expression. The type3 analysis of variance and the likelihood ratio tests of the variance component analyses indicated the existence of significant differences (p ≤ 0.01 or p ≤ 0.05) among RIL for all traits (Tables 3.1 and 3.2). Similarly, variance component analyses revealed significant (p ≤ 0.01 or p ≤ 0.05) location and location x family interactions effects for all traits. Spearman (rank) correlations between environments indicated, however, that the interactions between family and environment for all traits were mainly due to changes in trait magnitude in the locations examined (Table 3.3). Given the significant location and/or genotype x location interactions detected for all traits, data are hereafter presented by location. 174

PARENT AND RIL DATA. Graphic representations of yield and fruiting characteristics of the

USDA 846-1 (P1), “Top Mark” (P2), “Esteem” (ES), “Sol Dorado” (SD), “Hales Best Jumbo”

(HB) are presented in Appendix 4, and a sample of variation in the RIL population is presented in Appendixes III-1. Sex expression phenotypic scores of parental lines, control cultivars, and 81 RIL are presented in Table 3.4 and Appendix III-5. BLUPs and BLUEs,

S.E., C.I.s, tBLUPs, genotype scores, and genotype ranks of both parental lines, control cultivars, and 81 RIL for PB, FN, FW, AWF, and PMF are presented by location in Table 3.5 and Appendixes III-6 to III-15.

Sex expression in the parental lines, control cultivars, and the RIL population examined fluctuated as the season progressed in Wisconsin (EXS-W30, EXS-W45, and EXS-W60) and in the California trial (EXS-C45) (Table 3.4 and Appendix III-5). For example, at 30 days after transplant in Wisconsin (EXS-W30), P1 plants produced only staminate and pistillate flowers, P2 and ES plants produced staminate, pistillate and hermaphrodite flowers, and SD and HB plants produced staminate and hermaphrodite flowers. At 45 and 60 days after transplant in Wisconsin (EXS-W45 and EXS-W60), however, both parental lines and all controls produced plants having all three flower types. Conversely, at 45 days after sowing in California (EXS-C45), P1 produced only staminate and pistillate flowers while P2 and all control cultivars produced only staminate and hermaphrodite flowers. The frequency (%) of

RIL producing only staminate and pistillate flowers tended to decrease throughout the season in Wisconsin (EXS-W30 = 37 %, EXS-W45 = 37 %, EXS-W60 = 34 %), and this frequency was comparatively lower in California (EXS-C45 = 28 %). Similarly, the percentage of RIL 175 producing only staminate and hermaphrodite flowers decreased in Wisconsin from 53 %

(EXS-W30) to 34 % during the season (EXS-W60).

Differences in performance for FN, FW, AWF, and PMF were observed among highly branched fractal versus vining plant types at both locations (Table 3.5 and Appendixes 3 and

4). Individual RIL were observed that transgressed the performance of either parent for PB,

FN, FW, AWF, and PMF (Table 3.5; Appendixes III-2 to III-3 and III-6 to III-15). The

BLUE of P1 for PB, FN, and FW was consistently higher (p ≤ 0.05) than the BLUE of P2 and the RIL taken collectively, and the fruit yield of P1 was comparable to the control cultivars.

While the number of primary branches (PB) remained comparatively constant across locations (4.1, CA and 4.3, WI), fruit number per plant (FN; 4.3, CA and 1.9, WI) and fruit weight per plant (FW; 1.9 kg, CA and 1.0 kg, WI) were higher in California than in

Wisconsin (Table 3.5). The size of each fruit (AWF) was, however, comparatively smaller in

California (0.48 kg) than in Wisconsin (0.56 kg).

PHENOTYPIC CORRELATIONS. Phenotypic correlations between yield components are presented by location in Tables 3.6 and 3.7. Primary branch (PB) was positively correlated with FN (r = 0.27, CA; r = 0.55, WI), FW (r = 0.22, CA; r = 0.19, WI), and PMF (r = 0.23,

CA), and negatively correlated with AWF (r = - 0.32, CA; r = - 0.32, WI). Fruit number

(FN) was positively correlated with FW (r = 0.41, WI) and negatively correlated with AWF

(r = - 0.69, CA; r = - 0.51, WI). Fruit weight (FW) was positively correlated with AWF (r = -

0.64, CA; r = - 0.51, WI) and PMF (r = - 0.43, CA; r = - 0.42, WI). Average weight per fruit

(AWF) was positively correlated with PMF (r = - 0.30, WI). 176

HERITABILITIES ESTIMATES. Broad-sense heritabilities for PB, FN, FW, AWF, and PMF calculated using combined location data are presented in Tables 3.1 and 3.2. Broad-sense heritabilities were 0.84 for PB, 0.70 for FN, 0.55 for FW, 0.85 for AWF, and 0.64 for PMF.

LINKAGE ANALYSIS. Linkage analysis employing 116 RAPD, 41 SSR, and 33 AFLP markers resulted in a genetic melon map consisting of 15 linkage groups (LG1 to LG15;

Figure 3.1 and Appendix III-16). This map spans 1,032 cM consisting of 181 markers (114

RAPD, 35 SSR, and 32 AFLP), and nine unlinked markers (six SSR, two RAPD, and one

AFLP). While the mean marker interval was 5.7 cM, the largest interval between any two markers was 33.2 cM (E25M60-209 and E13M50-185; LG1). Four relatively small linkage groups were identified spanning 20 (LG12), 13 (LG13), 9 (LG14), and 7 (LG15) cM. Eleven linkage groups, LG1 to LG11, spanned 205, 158, 135, 104, 76, 69, 69, 54, 40, 39, and 36 cM, respectively.

While two RAPD markers (OPP7-550 and OPZ18-1375) remained unlinked, 114 were distributed in 15 linkage groups with four of them possessing codominant markers (OPAT1-

550, LG1; OPAB4-1375, LG6; OPA16-850, LG9; OPAI8-250, LG11). Similarly, one AFLP remained unlinked, and 32 were evenly distributed in 10 linkage groups (LG1 to LG6 and

LG8, LG9, LG14, and LG15). A total of 29 SSR primer pairs amplified a single polymorphic codominant locus, two (CMCT44 and CMCTT144) amplified one codominant and one dominant polymorphic loci each, and seven (TJ3, TJ19, TJ10, CMGA59,

CMTTAN28, CMGA127, and CMTC158) amplified one dominant polymorphic loci each. 177 Thus, a total of 31 codominant and 9 dominant polymorphic SSR loci were used for linkage analysis. The molecular weight of the 31 codominant SSR loci were within the expected range previously described (Danin-Poleg et al., 2001; Fazio et al., 2002; Gonzalo et al., 2005;

Katzir et al., 1996). The nine dominant SSRs markers were confirmed both on gel electrophoresis and by GeneScan analyses. Twenty-six of the codominant markers were distributed in eleven linkage groups (LG1 = 5, LG2 = 2; LG3 = 2, LG4 = 4, LG5 = 3, LG6 =

1, LG7 = 1, LG8 = 1, LG10 = 1, LG11 = 2, LG12 = 3, and LG14 = 1), and five were unlinked (CMCT44, CMTCN50, CMCTT144, CMTC168, and CMCTN38).

QTL MAPPING. Thirty-eight QTL were detected in both locations (EXS = 4, PB = 7, FN =

10, FW = 9, AWF = 5, and PMF = 3; Tables 3.8 and 3.9 and Appendix III-17 to III-33). The

38 QTL were distributed across 11 linkage groups (LG), such that eight were localized in

LG1, five in LG2, one in LG3, four in LG4, two in LG5, five in LG6, six in LG8, three in

LG9, one in LG10, one in LG11, and two in LG12. Fifteen (40%) of these QTL were detected consistently across locations. One QTL was consistently detected for EXS (exs8.3), four for PB (pb1.1, pb1.2, pb2.3, and pb10.5), three for FN (fn1.1, fn1.3, and fn5.6), four for

FW (fw1.1, fw5.6, fw6.7, and fw8.8), and two for AWF (awf1.2 and awf4.3). While, the proportion of the phenotypic variance explained by single QTL (R2) ranged from 4% (fn1.2) to 36% (exs8.3), major QTL (R2 ≥ 20%) were detected for EXS (exs4.1 and exs8.3), PB

(pb1.1), FW (fw5.6), and AWF (awf1.2). The direction of additive effects of QTLs was consistent across locations, and both parental lines contributed horticulturally desirable alleles for most traits. Line USDA 846-1 contributed alleles that were associated with 178 improved performance of most traits examined (exs4.1, exs8.3, pb1.1, pb11.6, pb12.7, fn1.1, fn1.3, fw2.3, awf4.3, and awf8.4).

TWO-DIMENSIONAL EPISTASIS GENOME SCANS. The presence of 97 pairs of putative QTL possessing joint-QTL epistatic effects and 38 pairs of putative QTL possessing interaction-

QTL epistatic effects were detected (Appendixes III-34 to III-45). Analyses of ESX, PB, and

FN revealed only joint-QTL epistatic effects (1, 13, and 8 pairs of putative QTL, respectively) involving mostly putative QTL in linkage groups and positions where QTLs had been previously identified using NP or/and CIM analyses (Tables 3.8 and 3.9 and

Appendixes III-17 to III-24). In contrast, analyses of FW, AWF, and PMF revealed interaction-QTL epistatic effects (23, 6, and 9 pairs of putative QTL, respectively) in addition to joint-QTL epistatic effects (27, 20, and 28 pairs of putative QTL, respectively) involving numerous putative QTL in linkage groups and positions where QTL had not been previously identified using CIM (Tables 3.9 and Appendixes III-25 to III-33).

Discussion

Empirical estimates of genetic parameters of yield components in melon are scarce (Lippert and Legg, 1972; Lippert and Hall, 1982), and their inheritance is complex (Tables 3.1 to 3.7;

Chapters I and II). Thus, breeding to increase yield in melon will likely require the incorporation of complicated phenotypic selection strategies. These strategies might be augmented by QTL analysis of yield components to facilitate MAS for the introgression of horticulturally preferred alleles into elite lines. This is the first QTL mapping analysis of 179 yield components in melon, and represents the initial steps required for the implementation of

MAS for the introgression of a unique, fractal growth habit into commercial germplasm.

A saturated melon genetic map is predicted to have a total length of between 1,500 to 2,000 cM distributed across 12 linkage groups (Baudracco-Arnas and Pitrat, 1996). However, most published melon maps span have identified more linkage groups than the basic chromosome number for this species (Baudracco-Arnas and Pitrat, 1996; Danin-Poleg et al., 2002; Liou et al., 1998; Silberstein et al., 2003; Wang et al., 1997; Table 2, Introduction). Similarly, the map developed herein consists of 15 linkage groups and nine unlinked markers, which indicates that this map is not completely saturated. Increasing the experimental population size and continued map saturation with codominant markers (markers at < 5 cM) should reduce sample variance (i.e., detect rare recombination events) and increase the map saturation of the genome (Liu, 1998a and 1998b) allowing for the merging of small linkage groups into the 12 expected chromosome complements.

Recently, Gonzalo et al. (2005) constructed a genetic map (“Songwhan Charmi” x “Pinyonet

Piel de Sapo”) consisting of 327 loci (226 RFLPs, 97 SSRs, and 3 SNPs) distributed over 12 linkage groups spanning 1,021 cM. Because SSRs provide common anchor points for sytenic analysis (Danin-Poleg et al., 2000, 2001; Katzir et al., 1996), the genetic map of

Gonzalo et al. (2005) has been proposed as a possible bridge with other melon maps containing common SSR markers. Périn et al. (2002c), in fact, showed the potential utility of

SSR markers in this regard. Common SSR markers were therefore used to cross-identify nine linkage groups identified herein (Figure 3.1) with equivalent linkage groups reported by 180 Gonzalo et al. (2005; designated by the prefix “G”). Linkage groups LG1 corresponded to

G1 (CMAT141 and CMGAN25), LG2 to G12 (CMTCN41 and CMTC123), LG3 to G6

(TJ27 and CMCT505), LG4 to G3 (CMGA15 and CMGAN21), LG5 to G9 (CSWCT01,

CMCTN19, and CMGA172), LG6 to G11 (CMTCN14), LG8 to G8 (TJ24), and linkage groups LG12 and LG13 corresponded to sections of G5 (CMATN22, CMCTN7, and

CMTCN1) and G7 (CMTCN62) of the Gonzalo et al. (2005) map. The collinearity of these linkage maps is indicative of the potential broad application of the map developed herein.

Moreover, the collinear order of common markers indicates that merging of these maps is possible, which would allow comparative QTL mapping in this species (Monforte et al.,

2003).

The significant positive phenotypic correlations observed (Tables 3.6 and 3.7) among PB,

FN, and FW, and negative phenotypic correlations between PB and AWF and between FN and AWF are consistent with previously reported correlations in diverse melon populations

(Abdalla and Aboul-Nasr, 2002; Kultur et al., 2001; Lippert and Hall, 1982; Taha et al.,

2003). The present QTL study confirmed such correlation data since yield component QTL identified in/or around the same genomic regions (Figure 3.1) were usually phenotypically correlated (Tables 3.6 and 3.7). Additional studies (i.e., fine mapping) will be necessary to determine whether such correlations are due to pleiotropy and/or linkage between loci

(Falconer and Mackay, 1996).

Increasing primary branch number in melon can theoretically increase total yield (Hughes et al., 1983; Kubicki, 1962; McGlasson and Pratt, 1963; Nerson, et al., 1983; Nerson and Paris, 181 1987; Paris et al., 1985). The empirical data (i.e., BLUEs and BLUPs) presented herein

(Tables 3.5 and Appendixes III-5 to III-15) provide evidence that highly branched, fractal melon types are capable of producing higher fruit number and weight per plant than standard vining types. This hypothesis is in agreement with the correlative relationships detected between PB and FN and FW observed herein (Tables 3.6 and 3.7) and other populations segregating for the fractal plant habit (Chapters I and II). Furthermore, four PB QTLs

(pb1.1, pb1.2, pb2.3, and pb8.4) were in close proximity to QTLs for FN (fn1.2, fn1.3, fn2.4, fn8.8, fn8.9, and Fn12.10) and FW (fw2.3, fw2.4, and fw8.8). Linkage Group 1 (LG1) is particularly interesting in this regard since a QTL for PB (pb1.1, contributed by USDA 846-

1) possessing positive additive effects, accounting for up to 20% of the phenotypic variance, was in close proximity to two QTL for FN (fn1.2 and fn1.3; R2 = 16%). Given the relatively high heritability estimates of PB reported herein (Table 3.1) and in Chapters I and II, and the fact that four QTL (pb1.1, pb1.2, pb2.3, and pb10.5) were consistently identified across locations accounting for up to 54% of the associated phenotypic variance, PB is an attractive candidate trait to for use in MAS for yield improvement in melon.

Horticulturally desirable alleles of metric traits can be present in both superior and inferior parents (Asíns, 2002). For instance, in cucumber QTL analysis of multiple lateral branch number in a RIL population indicated that a QTL in the low lateral branching parent (G421) contributed a positive effect for increased lateral branch number (Fazio et al. 2003a).

Similarly, a QTL (pb1.2) associated with increased primary branch number in the present study originated in the low branching parent (“Top Mark”). Allelic contributions from both parents and interaction between plant habit QTL likely resulted in the observed phenotypic 182 differences among the RIL. Such differences are probably due to the fractal nature of USDA

846-1, which is associated with a slightly more compact plant habit (Figure 3, Introduction) coupled with the more indeterminate growth habit of vining types.

The development of fractal genotypes capable of supporting three to four early maturing fruit while simultaneously maintaining commercially acceptable fruit size (0.7 to 1.2 kg) may be challenging given the negative correlations between fruit number per plant and average fruit weight (Tables 3.6 and 3.7; Chapters I and II). These phenotypically-based associations are consistent with the relative close proximity of genomic locations of AWF and FN QTL that possess contrasting additive effects. Nevertheless, a QTL associated with FN (fn1.1; LG1;

R2 = 12%) and a QTL associated with AWF (awf4.3; LG4; R2 = 16%) both contribute independent positive effects towards improved yield, and therefore could be used during

MAS augmented phenotypic selection to increase fruit number while maintaining commercially acceptable fruit size.

The number of yield component QTL identified in this melon population may have been underestimated due the relatively small size of the population used in this study (81 RIL) and/or to the low heritabilities of some traits (FW, AWF, and PMF; Tables 3.1 and 3.2;

Chapters I and II) (Beavis, 1998; Melchinger et al., 1998; Utz et al., 2000). Moreover, QTL analyses performed herein may have been unable to dissect closely linked QTL effects

(Lynch and Walsh, 1998; Mackay, 2001). Nevertheless, the results of these QTL analyses recapitulated the hypothesized quantitative nature of the yield components examined.

Furthermore, this QTL mapping effort corroborated the empirical estimates of number of 183 genomic regions affecting PB (~ 4), and provided a more accurate estimate of the number genes affecting FN, FW, AWF, and PMF than previously reported in Chapters I and II.

Epistatic QTL effects are important since they are indicative of multiple genomic regions conditioning the expression of target traits (Doerge, 2002). The detection of multiple epistatic interactions for yield components reported herein (Appendixes III-34 to III-45) confirms empirical findings regarding significant epistatic effects for most of the traits examined as obtained from generation means analyses (Chapter I). In fact, FW, AWF, and

PMF collectively possessed 84% of the putative pairs of epistatic QTL identified, which is indication that additional QTL with smaller effects are operating to control these traits in this population. Knowledge of such epistatic loci will be beneficial in the development of effective breeding strategies for the development of high yielding lines in this population.

The genetic control of sex expression in melon depends on three genes, andromonoecious (a;

Rosa, 1928), gynomonoecious (g; Poole and Grimball, 1939), and maleness (M; Keningsguch and Cohen, 1990). Given this current three-gene model (A, G, and M), monoecious (A-G-M- or A-G-mm) plants are expected to possess only staminate and pistillate flowers while andromonoecious (aaG-M- and aaG-mm) plants produce staminate and hermaphrodite flowers. However, sex expression in melon (Kenigsbuch and Cohen, 1989; Kubicki, 1969;

Rowe, 1969) and cucumber (Cantliffe, 1981; Fazio et al., 2003a; Dijkhuizen and Staub 2003;

Zhang et al., 1992) has been found to fluctuate due to environmental conditions (e.g., photoperiod and temperature), G x E interactions, and the action of modifying genes. 184

The RIL (F6) population used herein was derived from a P1 (AAGGMM) x P2 (aaGGMM) mating, and thus each RIL should theoretically be homozygous at the a locus such that the population would predictably be composed of 50% monoecious (i.e., AAGGMM) and 50% andromonoecious (i.e., aaBBCC) families. However, as many as 40% of the RIL examined changed sex expression (monoecious to andromonoecious or andromonoecious to monoecious) during the course of the growing season in Wisconsin and/or possessed inconsistent sex expression in California (Table 3.4 and Appendix III-5). Thus, given the theoretical genetic expectations of a RIL population (i.e., 97 % of the RIL homozygous at single loci), it is likely that the observed changes in sex expression are due to the effects of modifying genes and not to segregation at the a locus. This hypothesis is supported by the fact that both parental lines and the andromonoecious control cultivars (“Esteem”, “Sol

Dorado”, and “Hales Best Jumbo”) also showed similar changes in sex expression during the different measurement periods in Wisconsin (Table 3.4).

Given the observed sex expression changes in the RIL population examined herein, direct mapping of the a locus was not performed. Rather, the genetics of sex expression was examined using a non-parametric (NP; Kruklyak and Lander, 1995) model and composite interval mapping (CIM; Zeng, 1993; Zeng, 1994). Four QTL, accounting for up to 83% of the phenotypic variation, were detected for sex expression, exs4.1, exs6.2, exs8.3, and exs9.4.

Only one QTL, exs8.3, was consistently detected using both NP and CIM analyses across measurement periods and locations (i.e., EXS-W30, EXS-W45, EXS-W60, and EXS-C45).

This QTL, localized in linkage Group 8 (LG8; Figure 3.1), explained up to 36% (CIM; LOD

11.1; EXS-C45) of the phenotypic variation and was associated with a dominant RAPD 185 marker (OPAL9-750 with a band presence in USDA-846-1). Linkage Group 8 (LG8) corresponds (cross-identified using SSR TJ24) to G8 of the Gonzalo et al. (2005) map

(Figure 3.1). Although Gonzalo et al. (2005) did not map the a locus, previous studies have mapped this locus as a morphological codominant marker to linkage groups equivalent to G8

(Danin-Poleg et al., 2002, LGIV; Perin et al., 2002b, LGII; Silberstein et al., 2003, LG2).

The data presented herein provide support for the control of pistillate/hermaphroditic flowering at the a locus, and evidence that other genomic regions modify sex expression at this locus (Table 3.8, Figure 3.1, Appendixes III-17, III-18, III-34, and III-35). It is possible that the genomic regions identified in LG4 (exs4.1), LG6 (exs6.2), and LG9 (exs9.4) may operate to modify the action of the a locus under depending on environmental conditions

(e.g., temperature, humidity, and photoperiod in CA and WI). Moreover, the fact that these

QTL were detected in successive measurements (EXS-W45, EXS-W60, and EXS-C45) may indicate that the genes segregating for this trait in this cross had their greatest demonstrable physiological effect late in the season (Table 3.8, Figure 3.1, Appendixes III-17, III-18, III-

34, and III-35).

The principal objective for this QTL mapping effort was to identify candidate QTL for MAS to increase selection efficiency in melon. The effectiveness of selection using marker-trait associations has been demonstrated in cucumber (Fazio, 2001; Fazio et al., 2003b). In this case, MAS was as effective as phenotypic selection when selecting for multiple lateral branching. Similarly, the molecular markers associated with environmentally-independent

QTL for PB (pb1.1, pb1.2, pb2.3, and pb10.5) in the present study may prove useful in 186 breeding for increased yield in melon through the development of extreme fractal genotypes.

Moreover, QTL for EXS (exs4.1 and exs8.3), FN (fn1.1, fn1.3, and fn5.6), FW (fw1.1, fw5.6, fw6.7, and fw8.8), and AWF (awf1.2 and awf4.3) will likely assist in the development of early, high yielding cultivars with concentrated fruit set in this population through marker- assisted backcross methodologies. 2 Table 3.1. Analysis of variance, estimates of variance components, and broad-sense heritabilities (h B) of primary branch number (PBN), and fruit number (FN), and weight (kg; FW) per plant in 81 melon (Cucumis melo L.) recombinant inbred lines (RIL) derived from a cross between USDA 846-1 (P1) and “Top-Mark” (P2) grown at El Centro, California and Hancock, Wisconsin in 2002. Primary branch Fruit number per Fruit weight per number (PB) plant (FN) plant (kg; FW) Source of variation df 1 MS 2 df MS df MS Location (L) 1 7.88 n.s. 3 1 903.78 ** 1 133.58 ** Block (Location) [B(L)] 6 4.35 ** 6 3.77 ** 6 0.86 ** Family (F) 80 2.65 ** 80 4.71 ** 80 0.65 ** Family x Location (F x L) 80 0.44 ** 80 1.39 ** 80 0.29 ** Family x Block (Location) [F x B(L)] 478 0.27 472 0.35 472 0.07 Total 645 639 639 Variance Percent Variance Percent Variance Percent Source of variation component of total 4 component of total component of total Location (L) 0.01 ± 0.04 n.s. 1.6 2.82 ± 4.01 n.s. 72.5 0.42 ± 0.59 n.s. 69.6 Block (Location) [B(L)] 0.05 ± 0.03 n.s. 7.8 0.04 ± 0.03 n.s. 1.1 0.01 ± 0.01 n.s 1.7 Family (F) 0.28 ± 0.05 ** 42.7 0.42 ± 0.10 ** 10.7 0.05 ± 0.01 ** 7.6 Family x Location (F x L) 0.04 ± 0.02 ** 6.5 0.26 ± 0.06 ** 6.8 0.06 ± 0.01 ** 9.5 Family x Block (Location) [F x B(L)] 0.27 ± 0.02 ** 41.4 0.35 ± 0.02 ** 8.9 0.07 ± 0.00 ** 11.7 Total 0.65 100.00 3.89 100.00 0.60 100.00 2 h B = 0.84 ± 0.15 0.70 ± 0.17 0.55 ± 0.19 1 df = degrees of freedom. 2 MS = means square. 3 *, **, n.s. indicates that the effect is significant at p ≤ 0.05, p ≤ 0.01, and not significant, respectively. 4 Percent of variance component contribution to the total variance.

187 2 Table 3.2. Analysis of variance, estimates of variance components, and broad-sense heritabilities (h B) for average weight per fruit (kg; AWF) and percentage mature fruit per plot (PMF) in 81 melon (Cucumis melo L.) recombinant inbred lines (RIL) derived from a cross between USDA 846-1 (P1) and “Top-Mark” (P2) grown at El Centro, California and Hancock, Wisconsin in 2002. Average weight per fruit (kg; AWF) Percentage mature fruit per plot (PMF) Source of variation df 1 MS 2 df MS Location (L) 1 1.06 ** 3 1 83437.00 ** Block (Location) [B(L)] 6 0.01 * 6 1641.88 ** Family (F) 80 0.18 ** 80 1039.76 ** Family x Location (F x L) 80 0.03 ** 80 369.40 ** Family x Block (Location) [F x B(L)] 472 0.01 472 138.90 Total 639 639 Variance Percent Variance Percent Source of variation component of total 4 component of total Location (L) 0.0032 ± 0.0047 n.s. 9.6 254.11 ± 367.60 n.s. 45.9 Block (Location) [B(L)] 0.0001 ± 0.0001 n.s. 0.2 18.66 ± 11.77 n.s. 3.4 Family (F) 0.0190 ± 0.0036 ** 56.6 84.31 ± 21.96 ** 15.2 Family x Location (F x L) 0.0052 ± 0.0011 * 15.5 58.16 ± 14.88 ** 10.5 Family x Block (Location) [F x B(L)] 0.0061 ± 0.0004 ** 18.1 138.82 ± 9.01 ** 25.1 Total 0.0336 100.00 554.06 100.0 2 h B = 0.85 ± 0.16 0.64 ± 0.16 1 df = degrees of freedom. 2 MS = means square. 3 *, **, n.s. indicates that the effect is significant at p ≤ 0.05, p ≤ 0.01, and not significant, respectively. 4 Percent of variance component contribution to the total variance.

188 Table 3.3. Correlation (rank) coefficients (rs) between locations (El Centro, California and Hancock, Wisconsin, 2002) for yield components in 81 melon (Cucumis melo L.) recombinant inbred lines (RIL) derived from a cross between USDA 846-1 (P1) and “Top-Mark” (P2). Trait EC vs. HCK (r) 1 Primary branch number (PB) 0.73 *** 2 Fruit number per plant (FN) 0.59 *** Fruit weight per plant (kg; FW) 0.48 *** Average weight per fruit (kg; AWF) 0.74 *** Percentage of plants with early maturing fruit/plot (PMF) 0.47 *** 1 Spearman correlations (rank) coefficients (rs) calculated using the tBLUPs values of RIL for each individual trait between locations (Appendixes III-6 to III-15). 2 Significant at p ≤ 0.01.

189 Table 3.4. Sex expression phenotypic scores of USDA 846-1 (P1), “Top Mark”(P2), “Esteem” (ES), “Sol Real” (SR), “Hales Best Jumbo” (HB), and 81 melon (Cucumis melo L.) recombinant inbred lines (RIL; P1 x P2), and their standard errors (S.E.) evaluated in El Centro, California and Hancock, Wisconsin in 2002. 2 Trait P1 P2 ES SR HB RIL percentage Sex expression in Wisconsin 30 days after transplant (EXS-W30) 1 M H/M H/M H H M % = 37, A % = 53, A/M % =10 Sex expression in Wisconsin 45 days after transplant (EXS-W45) 1 H/M H/M H/M H/M H/M M % = 37, A % = 35, A/M % = 28 Sex expression in Wisconsin 60 days after transplant (EXS-W60 ) 1 H/M H/M H/M H/M H/M M % = 34, A% = 34, A/M % = 32 Sex expression in California 45 days after sowing (EXS-C45) 1 M H H H H M % = 28, A % = 53, A/M %= 19 1 EXS-W30 = sex expression taken in Wisconsin at 30 days after transplant; EXS-W45 = sex expression taken in Wisconsin at 45 days after transplant; EXS-W60 = sex expression taken in Wisconsin at 60 days after transplant; EXS-C45 = sex expression taken in California at 45 days after sowing. Sex expression scores: H = plots contain only hermaphrodite and staminate flowers; H/M = plots contain hermaphrodite, pistillate, and staminate flowers; and M = plots contain only pistillate and staminate flowers. 2 M % = percentage of RIL possessing only pistillate and staminate flowers, H % = percentage of RIL possessing only hermaphrodite and staminate flowers, and H/M = percentage of RIL possessing hermaphrodite, pistillate and staminate flowers (Appendix III-5).

190 Table 3.5. Best linear unbiased estimations (BLUEs) of USDA 846-1 (P1), “Top Mark”(P2), “Esteem” (ES), “Sol Real” (SR), and “Hales Best Jumbo” (HB), and best linear unbiased predictions (BLUPs) of a melon (Cucumis melo L.) RIL population, their standard errors (S.E.), and confidence intervals (C.I.) for yield components based on plants grown at El Centro, California and Hancock, Wisconsin in 2002. Hancock, WI BLUE BLUP C.I. (95 %) . . Trait P1 P2 ES SR HB RIL Lower Upper Primary branch number (PB) 5.33 ** 3.45 ** 4.25 n.s. 3.75 ** 3.63 ** 4.30 ± 0.11 3.96 4.64 Fruit number/plant (FN) 2.33 ** 2.13 n.s. 1.78 n.s. 2.40 ** 1.78 n.s. 1.92 ± 0.0 1.64 2.20 Fruit weight/plant (kg; FW) 1.35 ** 1.22 ** 1.62 ** 1.38 ** 1.66 ** 1.01 ± 0.03 0.90 1.12 Average weight/fruit (kg; AWF) 0.58 n.s. 0.58 n.s. 0.93 ** 0.60 n.s. 0.93 ** 0.56 ± 0.02 0.50 0.62 Percentage of mature fruit/plot (PMF) 88.75 ** 87.50 ** 88.75 ** 76.25 ** 92.50 ** 60.06 ± 2.01 53.67 66.46 El Centro, CA BLUE BLUP C.I. (95 %) . . Trait P1 P2 ES SR HB RIL Lower Upper Primary branch number (PB) 5.70 ** 3.58 ** 2.96 ** 3.23 ** 3.10 ** 4.08 ± 0.15 3.59 4.57 Fruit number/plant (FN) 5.55 ** 3.86 n.s. 4.27 n.s. 3.47 n.s. 2.62 n.s. 4.30 ± 0.18 3.72 4.88 Fruit weight/plant (kg; FW) 2.55 ** 2.00 n.s. 2.94 ** 2.41 ** 2.14 n.s. 1.93 ± 0.08 1.66 2.19 Average weight/fruit (kg; AWF) 0.47 n.s. 0.52 n.s. 0.74 ** 0.70 ** 0.81 ** 0.48 ± 0.02 0.42 0.53 Percentage of mature fruit/plot 82.86 ± 3.11 (PMF) 87.50 n.s. 88.75 n.s. 92.50 n.s. 100.00 ** 97.52 ** 72.96 92.77 1 **, the BLUEs of a parental line (P1 and P2) and/or “Esteem’, “Sol Real” and “Hales Best Jumbo” considered significantly different (p ≤ 0.05) from the average of the RIL when values were outside the C.I. limit of the RIL population BLUPs. 2 n.s., the BLUEs of the a parental line, their hybrid, and/or “Hales Best Jumbo” considered not significantly different (p ≥0.05) from the average of the RIL when values were within the C.I. limit of the RIL population BLUPs.

191 Table 3.6. Phenotypic correlations among yield components in 81 melon (Cucumis melo L.) recombinant inbred lines (RIL) derived from a cross between USDA 846-1 (P1) and “Top-Mark” (P2) evaluated at Hancock, Wisconsin in 2002. Primary branch Fruit number Fruit weight Average weight Percentage of number per plant per plant per fruit mature fruit per Trait (PB) (FN) (kg; FW) (kg; AWF) plot (PMF) PB - 0.55 *** 0.19 * -0.32 *** 0.13 n.s. FN - 0.41 *** -0.51 *** 0.40 *** FW - 0.51 *** 0.42 *** AWF - 0.03 n.s. PMF - 1 n.s.,*,**,***, and non-significant or significant at p ≤ 0.05, 0.01, and 0.001.

192 Table 3.7. Phenotypic correlations among yield components in 81 melon (Cucumis melo L.) recombinant inbred lines (RIL) derived from a cross between USDA 846-1 (P1) and “Top-Mark” (P2) evaluated at El Centro, California in 2002. Primary branch Fruit number Fruit weight Average weight Percentage of number per plant per plant per fruit mature fruit per Trait (PB) (FN) (kg; FW) (kg; AWF) plot (PMF) PB - 0.27 *** 0.22 * -0.32 *** 0.23 * FN - 0.04 n.s. -0.69 *** 0.00 n.s. FW - 0.64 *** 0.43 *** AWF - 0.30 *** PMF - 1 n.s.,*,**,***, and non-significant or significant at p ≤ 0.05, 0.01, and 0.001.

193 Table 3.8. Linkage group (LG) positions (cM) of QTL along with their associated logarithm of odds (LOD), percentage of phenotypic variation (R2), and additive effect for sex expression in a recombinant inbred line (RIL) population derived from a cross between melon (Cucumis melo L.) lines USDA 846-1 and “Top Mark” evaluated in Hancock, Wisconsin and El Centro, California in 2002. Linkage Trial Position Nearest NP CIM Additive Parent group QTL 1 Location 2 (cM) marker locus 3 LOD 4 LOD 5 R2 (%) effect 6 effect 6

LG4 exs4.1 EXS-W45 26 CMGA15 - 2.99 0.20 0.42 P1

LG4 exs4.1 EXS-W60 28 CMGA15 3.00 6.21 0.28 0.72 P1

LG4 exs4.1 EXS-C45 27 CMGA15 2.95 6.55 0.27 0.69 P1

LG6 exs6.2 EXS-W45 50 OPAB4-1375 - 3.27 0.10 -0.33 P2

LG6 exs6.2 EXS-W60 50 OPAB4-1375 - 3.56 0.09 -0.31 P2 48 LG8 exs8.3 EXS-W30 OPAL9-750 3.60 6.57 0.25 0.51 P1 48 LG8 exs8.3 EXS-W45 OPAL9-750 3.70 6.82 0.22 0.46 P1 48 LG8 exs8.3 EXS-W60 OPAL9-750 3.80 6.53 0.18 0.40 P1 48 LG8 exs8.3 EXS-C45 OPAL9-750 3.80 11.12 0.36 0.53 P1

LG9 exs9.4 EXS-W60 25 OPAI17-750 - 3.28 0.09 -0.36 P1

LG9 exs9.4 EXS-C45 25 OPAI17-750 - 3.06 0.08 -0.35 P1 1 QTL designated by the abbreviated trait name (EXS = sex expression), linkage group number and QTL number. 2 EXS recorded in Wisconsin at 30 (EXS-W30), 45 (EXS-W45), and 60 (EXS-W60) days after transplant, and California 45 (EXS-C45) days after sowing. 3 Nearest marker to peak of the detected QTL. 4 NP = non-parametric model resident in R/qtl (Broman et al. 2003), respectively. 5 CIM = composite interval mapping resident in Windows QTL Cartographer 2.0 (Wang et al. 2001-2004). 6 Additive effect as obtained from a composite interval mapping (CIM) model resident in QTL cartographer (Wang et al. 2001-2004). 7 Parent responsible for the additive effect.

Table 3.9. Linkage group (LG) positions (cM) of QTL along with their associated logarithm of odds (LOD), percentage of phenotypic variation (R2), and additive effect for yield components in a recombinant inbred line (RIL) population derived from a 194 cross between melon (Cucumis melo L.) lines USDA 846-1 and “Top Mark” evaluated in Hancock, Wisconsin and El Centro, California in 2002. Linkage Trial Position Nearest Additive Parent Trait 1 group QTL 2 location (cM) marker locus 3 Flanking markers 3 LOD R2 (%) effect 4 effect 5

PB LG1 pb1.1 WI 56 OPI11-500 OPAY16-400 - OPAE3-600 3.46 0.13 0.26 P1

LG1 pb1.1 CA 56 OPI11-500 OPAY16-400 - OPAE3-600 8.85 0.20 0.25 P1

LG1 pb1.2 WI 152 OPF4-850 CMGAN25 - DoCMTTAN28-170 6.96 0.15 0.21 P2

LG1 pb1.2 CA 151 BC526-831 OPR3-831 - CMGAN25 5.99 0.13 0.19 P2

LG2 pb2.3 WI 117 E13M51-284 OPAI8-800 - E19M47-329 3.40 0.10 -0.17 P2

LG2 pb2.3 CA 119 E13M51-284 OPAI8-800 - E19M47-329 2.54 0.08 -0.15 P2

LG8 pb8.4 WI 19 OPAL8-400 TJ24 - E13M51-203 2.82 0.05 -0.13 P2

LG10 pb10.5 WI 6 OPAB4-750 OPAD19-550 2.84 0.06 -0.13 P2

LG10 pb10.5 CA 1 OPAB4-750 OPAD19-550 2.78 0.05 -0.13 P2

LG11 pb11.6 CA 5 OPAI11-550 CMGA104 2.82 0.06 0.13 P1

LG12 pb12.7 CA 20 CMCTN7 OPK4-564 - CMTCN1 3.80 0.08 0.15 P1

FN LG1 fn1.1 WI 16 TJ22 OPAY1-831 - OPAA10-1000 6.01 0.12 1.99 P1

LG1 fn1.1 CA 16 TJ22 OPAY1-831 - OPAA10-1000 3.48 0.11 3.26 P1

LG1 fn1.2 CA 61 OPP8-564 OPAE3-600 - OPAK14-1500 3.33 0.04 2.63 P2

LG1 fn1.3 WI 127 E14M49-100 OPAD19-1200 - CMAT141 6.24 0.14 2.06 P1

LG1 fn1.3 CA 121 E14M49-100 OPAD19-1200 - CMAT141 7.04 0.12 3.87 P1

LG2 fn2.4 CA 103 OPAI8-800 BC299-650 - E13M51-284 8.84 0.14 4.34 P2

LG4 fn4.5 WI 71 E24M17-91 OPAD15-830 - CMGAN21 2.69 0.07 -1.43 P1

Table 3.9. (continued). Linkage Trial Position Nearest Additive Parent

195 Trait 1 group QTL 2 location (cM) marker locus 3 Flanking markers 3 LOD R2 (%) effect 4 effect 5

FN LG5 fn5.6 WI 45 CMGA172 E26M48-265 - E26M48-264 3.37 0.06 -1.34 P2

LG5 fn5.6 CA 48 CMGA172 E26M48-265 - E26M48-264 5.07 0.08 -4.26 P2

LG6 fn6.7 WI 56 OPAG15-570 OPAX6-831 - OPAM14-1380 3.04 0.06 -1.72 P1

LG8 fn8.8 WI 19 OPAL8-400 TJ24 - E13M51-203 2.69 0.05 -1.25 P2

LG8 fn8.9 CA 53 OPAL9-750 OPAR1-1300 - E14M50-159 4.21 0.06 -2.74 P1

LG12 fn12.10 WI 1 CMATN22 OPK4-564 2.61 0.05 -1.18 P2

FW LG1 fw1.1 WI 101 OPAT1-550 OPAK14-1500 - OPAD19-1200 3.50 0.08 -0.61 P1

LG1 fw1.1 CA 113 OPAD19-1200 OPAT1-550 - E14M49-100 2.97 0.04 -1.04 P1

LG2 fw2.2 WI 27 OPAT1-575 OPAE2-1250 - CMTCN41 4.69 0.09 -0.70 P2

LG2 fw2.3 WI 55 OPU15-564 OPAG15-600 - OPAX6-400 3.91 0.12 0.86 P1

LG2 fw2.4 CA 90 OPR11-700 OPS12-1300 - CMTC123 4.23 0.08 1.14 P2

LG3 fw3.5 WI 36 DoTJ19-100 TJ27 - OPAC11-570 5.26 0.11 -0.78 P1

LG5 fw5.6 WI 57 E26M48-264 CMGA172 - DoCMCTT144-100 4.73 0.09 -0.66 P1

LG5 fw5.6 CA 46 E26M48-264 CMGA172 - DoCMCTT144-100 11.06 0.21 -1.80 P1

LG6 fw6.7 WI 56 OPAG15-570 OPAX6-831 - OPAM14-1380 2.51 0.04 -0.48 P1

LG6 fw6.7 CA 49 OPAB4-1375 E13M51-139 - OPAX6-831 3.68 0.07 -1.00 P1

LG8 fw8.8 WI 21 OPAL8-400 TJ24 - E13M51-203 5.92 0.13 -1.04 P2

LG8 fw8.8 CA 20 OPAL8-400 TJ24 - E13M51-203 2.68 0.08 -0.79 P2

LG9 fw9.9 CA 28 OPAD16-850 OPAI17-750 - E25M17-165 3.79 0.08 -1.52 P2

Table 3.9. (continued). Linkage Trial Position Nearest Additive Parent Trait 1 group QTL 2 location (cM) marker locus 3 Flanking markers 3 LOD R2 (%) effect 4 effect 5

AWF LG1 awf1.1 CA 61 OPP8-564 OPAE3-600 - OPAK14-1500 3.88 0.09 -0.47 P2 196 LG1 awf1.2 WI 134 CMAT141 E14M49-100 - E18M58-186 10.09 0.28 -0.94 P1

LG1 awf1.2 CA 128 E14M49-100 OPAD19-1200 - CMAT141 7.06 0.21 -0.71 P1

LG4 awf4.3 WI 18 CMGA15 CMGAN48 - E19M54-248 3.42 0.16 0.69 P1

LG4 awf4.3 CA 37 E19M54-248 CMGAN48 - E19M54-248 3.42 0.16 0.69 P1

LG8 awf8.4 WI 54 OPAL9-750 OPAR1-1300 - E14M50-159 4.16 0.08 0.50 P1

LG9 Awf9.5 CA 28 OPAD16-850 OPAI17-750 - E25M17-165 2.98 0.09 -0.56 P1

PMF LG4 pfm4.1 WI 95.61 E19M51-302 E14M48-140 - OPY5-1250 3.67 0.13 -4.57 P1

LG6 pfm6.2 WI 20.51 CMTCN14 E24M17-299 - E13M51-141 3.88 0.15 -4.82 P2

LG6 pfm6.3 WI 59.61 OPAM14-1380 OPAG15-570 - OPAL9-1100 4.16 0.12 -3.21 P2 1 Abbreviation of trait name where PB = primary branch number; FN = fruit weight/plot; FW = fruit weight/plot; AWF = average weight/fruit; and PFM = percentage of mature fruit/plot. 2 QTL designated by abbreviated trait name, linkage group number, and QTL number. 3 Nearest marker to peak of the detected QTL, and markers flanking the nearest marker to peak of the detected QTL. 4 Additive effect as obtained from a composite interval mapping (CIM) model resident in QTL cartographer (Wang et al. 2001-2004). 7 Parent responsible for the additive effect.

197 198 Figure 3.1. Linkage map1 and locations of quantitative trait loci (QTL) associated with yield components based on 81 melon (Cucumis melo L.) recombinant inbred lines (RIL) derived form a cross between USDA 846-1 and “Top Mark”. LG1 LG2 (1) (12)

fw2.2 fn1.1 CMTCN41

CMGAN12

CMATTN29 fw2.4 pb1.1 CMTC123 awf1.1 pb2.3 fn1.2 fn2.4

fw1.1 fn1.3 CMAT141 awf1.2

CMGAN25 pb1.2

LG4 TJ27 (3)

CMGAN48 LG3 CMGA15 awf4.3 exs4.1 (6) fn4.5 TJ27 fw3.5 CMGA21 TJ38

Pfm4.1 CMCT505

CMCT505 Sex expression Primary branch number Fruit number per plant Fruit weight per plant Average weight per fruit Percentage of mature fruit per plot

1Linkage groups designated LG followed by the linkage group number (e.g., LG1), and numbers inside parenthesis (1–12) correspond to linkage groups according to Oliver et al., 2001 and Gonzalo et al., 2005. Underlined markers are SSR markers from Katzir el al, 1996, Danin-Poleg et al., 2001, Fazio et al., 2002, and Gonzalo et al., 2005 (Appendix III-16).

Figure 3.1 (continued). 198 199

LG5 LG6 (9) (11)

CSWCT01 pfm6.2 CMTCN14 fn5.6 fw5.6 CMGA172 exs6.2 fn6.7 fw6.7

pfm6.3

CMTCN40 LG8 (8)

pb8.4 fn8.8 fw8.8

fn9.9 awf8.4 exs8.3 LG9 exs9.4 fw9.9 awf9.5 LG10 pb10.5

CMTCN9 LG11 (5) pb11.6 LG12 CMGA104 (7) fn12.10 CMATN22

CMTCN7 pb12.7

CMTCN1 LG13

CMTCN62 LG14

Sex expression Primary branch number Unlinked Fruit number per plant RAPD : OPP7-550, OPZ18-1375 Fruit weight per plant AFLP: E16M54-79 Average weight per fruit SSR : CMCT44, CMTCN50, CMCTT144, Percentage of mature fruit per plot CMTC168, CMCTN38, DoCMAGN39-150

Abdalla, M. M. A. and M. H. Aboul-Nasr. 2002. Estimation of heterosis for yield and other economical characters of melon (Cucumis melo L.) in upper Egypt. p. 11-16. In: Maynard, D. N. (ed.). Proc. Cucurbitaceae 2002. Naples, Florida, December 8-12, 2002. ASHS, Alexandria, VA. 199 200

Asíns, M. J. 2002. Present and future of quantitative trait locus analysis in plant breeding. Plant Breed. 121:281-291.

Bains, M. S. and U. S. Kang. 1963. Inheritance of some flower and fruit characters in muskmelon. Indian J. Genet. Plant Breed. 23:101-106.

Baudracco-Arnas, S. and M. Pitrat. 1996. A genetic map of melon (Cucumis melo L.) with RFLP, RAPD, isozyme, disease resistance and morphological markers. Theor. Appl. Genet. 93:57-64.

Beavis, W. D. 1998. QTL analysis: power, precision, and accuracy. p. 145-162. In: Paterson, A. H. (ed). Molecular dissection of complex traits. CRC Press, Boca Raton, FL.

Bernardo, R. 1998. Predicting the performance of untested single crosses: trait and marker data. In: Lamkey, K. R. and J. E. Staub (eds.). Proc. of the plant breeding symposium: Concepts and breeding of heterosis in crop plants. Nov. 3, 1998. Crop Science Society of America, Madison, WI.

Borevitz, J. O., J. N. Maloof, J. Lutes, T. Dabi, J. L. Redfern, G. T. Trainer, J. D. Werner, T. Asami, C. C. Berry, D. Weigel, and J. Chory. 2002. Quantitative trait loci controlling light and hormone response in two accessions of Arabidopsis thaliana. Genetics 160:683-696.

Broman, K.W., H. Wu, S. Sen, and G. A. Churchill. 2003. R/qtl: QTL mapping in experimental crosses. Bioinformatics 19:889-890.

Cantliffe, D. J. 1981. Alteration of sex expression in cucumber due to changes in temperature, light intensity, and photoperiod. J. Amer. Soc. Hort. Sci. 106:133–136.

Comstock, R. E. 1978. Quantitative genetics in maize breeding. p. 191-206. In: Maize breeding and genetics, New York.

Comstock, R. E. and H. F. Robinson. 1948. The components of genetic variance in populations of biparental progenies and their use in estimating the average degree of dominance. Biometrics 4:254-266.

Comstock, R. E. and H. F. Robinson. 1952. Estimation of average dominance of genes. p. 494-516. In: Gowen, H. W. (ed) Heterosis. Iowa State College Press, Ames, IA.

Churchill, G. A. and R. W. Doerge. 1994. Empirical threshold values for quantitative mapping. Genetics. 138:963-971.

Danin-Poleg, Y., N. Reis, S. Baudracco-Arnas, M. Pitrat, J. E. Staub, M. Oliver, P. Arus, C. M. deVincente, and N. Katzir. 2000. Simple sequence repeats in Cucumis mapping and map merging. Genome 43:963-974

200 201 Danin-Poleg, Y., N. Reis, G. Tzuri, and N. Katzir. 2001. Development and characterization of microsatellite in Cucumis. Theor. Appl. Genet. 102:61-72.

Danin-Poleg, Y., Y. Tadmor, G. Tzuri, N. Reis, J. Hirschberg, and N. Katzir. 2002. Construction of a genetic map of melon with molecular markers and horticultural traits, and localization of genes associated with ZYMV resistance. Euphytica. 125:373-384. de Leon, N., J. G. Coors, S. M. Kaeppler, G. J. M. Rosa. 2005. Genetic control of prolificacy and related traits in the golden glow maize population: I. phenotypic evaluation. Crop Sci. In Press.

Denna, D. W. 1962. A study of the genetic, morphological and physiological basis of the bush and vine habit of several cucurbits. Ph.D. Diss., Cornell University, Ithaca, NY.

Development Core Team. 2003. R.1.8.1- A language and environment for statistical computing. R Foundation for Statistical Computing. Vienna, Austria.

Dijkhuizen, A. and J. E. Staub. 2003. Effects of environment and genetic background on QTL affecting yield and fruit quality traits in a wide cross in cucumber [Cucumis sativus L. x Cucumis hardwickii (R.) Alef.]. J. New Seeds. 4:1-3.

Doerge, R. W. 2002. Mapping and analysis of quantitative trait loci in experimental populations. Nat. Rev. Genet. 3:43-52.

Dogimont, C., L. Leconte, C. Périn, A. Thabuis, H. Lecoq, and M. Pitrat. 2000. Identification of QTLs contributing to resistance to different strains of cucumber mosaic cucumovirus in melon. Acta Hortic. 510:391–398.

Dudley, J. W. and R. H. Moll. 1969. Interpretation and use of heritability and genetic estimates in plant breeding. Crop Sci. 9:257-262.

Eberhart, S. A. and C. O. Gardner. 1966. A general model for genetic effects. Biometrics 22:864-881.

Falconer, D. S. and T. F. C. Mackay. 1996. Introduction to quantitative genetics. 4th ed. Longman Group, London, UK.

Fazio, G. 2001. Comparative study of marker-assisted and phenotypic selection and genetic analysis of yield components in cucumber. Ph.D. Diss., University of Wisconsin, Madison.

Fazio, G., J. E. Staub, and S. M. Chung. 2002. Development and characterization of PCR markers in cucumber (Cucumis sativus L.). J Amer. Soc. Hort. Sci. 127:545–557.

Fazio, G., J. E. Staub, and M. R. Stevens. 2003a. Genetic mapping and QTL analysis of horticulture traits in cucumber (Cucumis sativus L.) using recombinant inbred lines. Theor. Appl. Genet. 107:864-874.

201 202

Fazio, G., S. M. Chung, and J. E. Staub. 2003b. Comparative analysis of response to phenotypic and marker-assisted selection for multiple lateral branching in cucumber (Cucumis sativus L.). Theor. Appl. Genet. 107:875-883.

Fulton, T. M., T. Beckbunn, D. Emmatty, Y. Eshed, J. Lopez, V. Petiard, J. Uhlig, D. Zamir, and S .D. Tanksley. 1997. QTL analysis of an advanced backcross of Lycopersicon peruvianum to the cultivated tomato and comparisons with QTLs found in other wild species. Theor. Appl. Genet. 95:881-894.

Galmarini, C. R., I. L. Goldman, and M. J. Havey. 2001.Genetic analyses of correlated solids, flavor, and health-enhancing traits in onion (Allium cepa L.) Mol. Genet. Genom. 265:543-551.

Gonzalo, M. J., M. Oliver, J. Garcia-Mas, A. Monfort, R. Dolcet-Sanjuan, N. Katzir, P. Arús, and A. J. Monforte. 2005. Development of a consensus map of melon (Cucumis melo L.) based on high-quality markers (RFLPs and SSRs) using F2 and double-haploid line populations. Theor. Appl. Genet. In Press.

Gardner, C. O. and S. A. Eberhart. 1966. Analysis and interpretation of the variety cross diallel and related populations. Biometrics 22:439-452.

Griffing, B. 1956. A Generalized treatment of the use of diallel crosses in quantitative inheritance. Heredity 10:30-50.

Haley, C. S. and S. A. Knott. 1992. A simple regression method for mapping quantitative trait loci in line crosses using flanking markers. J. Heredity 69:315-324.

Hallauer, A. R. and J. B. Miranda. 1988. Quantitative genetics and maize breeding, Iowa State University Press, Ames.

Hughes, D. L., J. Bosland, and M. Yamaguchi. 1983. Movement of photosynthates in muskmelon plants. J. Amer. Soc. Hort. Sci. 108:189-192.

Jones, E. S., A. Breese, C. J. Liu, S. D. Singh, D. S. Shaw, and J. R. Witcombe. 2002. Mapping quantitative trait loci for resistance to downy mildew in pearl millet: field and glasshouse screens detect the same QTL. Crop Sci. 42:1316-1323.

Jonhson, R. 1996. Statistics 7th ed. Duxbury Press. Belmont, CA.

Katzir, N., T. Danin-Poleg, G. Tzuri, Z. Karchi, U. Lavi, and P. B. Cregan, 1996. Length polymorphism and homologies of microsatellites in several Cucurbitaceae species. Theor. Appl. Genet. 93: 1282-1290.

Kearsey, M. J. and H. S. Pooni, 1996. The genetical analysis of quantitative traits, 1st ed. Chapman and Hall, London.

202 203

Kenigsbuch, D. and Y. Cohen. 1990. The inheritance of gynoecy in muskmelon. Genome 33:317-320.

Krakowsky, M. D., M. Lee, H. H. Beeghly, and J. C. Coors. 2003. Characterization of quantitative trait loci affecting fiber and lignin in maize (Zea mays L.). Maydica 48:283-292.

Kruklyak, L. and E. S. Lander. 1995. A nonparametric approach for mapping quantitative trait loci. Genetics 139:1421-1428.

Kubicki, B. 1962. Inheritance of some characters in muskmelon (Cucumis melo L.). Genet. Pol. 3:265-274.

Kubicki, B. 1969. Sex determination in muskmelon (Cucumis melo L.). Genet. Pol. 10:145- 165.

Kultur, F., H. C. Harrison, J. E. Staub, and J. P. Palta. 2001. Spacing and genotype effects on fruit sugar concentration and yield of muskmelon. HortScience 36:274-278.

Lande, R. 1981. The minimum number of genes contributing to quantitative variation between and within populations. Genetics 99:541-553.

Lande, R. and R. Thompson. 1990. Efficiency of marker-assisted selection in the improvement of quantitative traits. Genetics 124:743-756.

Lander, E., P. Green, J. Abrahamson, A. Barlow, M. Daly, S. Lincoln, and L. Newburg. 1987. MAPMAKER: An interactive computer package for constructing primary genetic linkage maps of experimental and natural populations. Genomics 1:174-181.

Lippert, L. F. and M. O. Hall. 1982. Heritabilities and correlations in muskmelon from parent offspring regression analyses. J. Amer. Soc. Hort. Sci. 107:217-221.

Lippert, L. F. and P. D. Legg. 1972. Diallel analysis for yield and maturity characteristics in muskmelon cultivars. J. Amer. Soc. Hort. Sci. 97:87-90.

Littell, R. C., G. A. Milliken, W. W. Stroup, and R. D. Wolfinger. 1996. SAS system for mixed models. SAS Institute Inc. Cary, NC.

Liou, P. C., Y. M. Chang, W. S. Hsu, Y. H. Cheng, H. R. Chang, and C. H. Hsiao. 1998. Construction of a linkage map in Cucumis melo (L.) using random amplified polymorphic DNA markers, p. 123-131. In: R.A. Drew (ed.). Proc. International symposium in biotechnololy: tropical and subtropical species.

Liu, B. H. 1998a. Statistical genomics: linkage, mapping, and QTL analysis. CRC Press, Boca Raton. New York.

203 204 Liu, B. H. 1998b. Computational tools for study of complex traits. p. 43-80. In: Paterson, A. H. (ed). Molecular dissection of complex traits. CRC Press, Boca Raton, NY.

Lynch, M. and B. Walsh. 1998. Genetics and analysis of quantitative traits. Sinauer Associates Inc., Sunderland, Mass.

Mackay, T. F. C. 2001. The genetic architecture of quantitative traits. Ann. Rev. Genet. 35:303-339.

Mandelbrot, B. B. 1983. The fractal geometry of nature. W. H. Freeman & Co. New York.

Marques, C. M., J. A. Araujo, J. G. Ferreira, R. Whetten, D. M. O’Malley, B. H. Liu, and R. Sederoff. 1998. AFLP genetic maps of Eucalyptus globules and E. tereticornis . Theor. Appl. Genet. 96:727-737.

Marquez-Cedillo, L. A., P. M. Hayes, B. L. Jones, A. Kleinhofs, W. G. Legge, B. G. Rossnagel, K. Sato, E. Ullrich, and D. M. Wesenberg. 2000. QTL analysis of malting quality in barley based on the doubled-haploid progeny of two elite North American varieties representing different germplasm groups. Theor. Appl. Genet. 101:173-184.

Mather, K. 1949. Biometrical genetics, 1st ed. Methuen, London.

Mather, K. and J. L. Jinks. 1971. Biometrical genetics. Cornell University Press, Ithaca, New York.

McGlasson, W. B. and H. K. Pratt. 1963. Fruit-set patterns and fruit growth in cantaloupe (Cucumis melo L. var. reticulatis Naud.). Proc. Amer. Soc. Hort. Sci. 83:495-505.

Melchinger, A. E., H. F. Utz, and C. C. Schon. 1998. 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. Genetics 149:383-403.

Mohr, H. C. and D. E. Knavel. 1966. Progress in the development of short-internode (bush) cantaloupes. HortScience 1:16.

Monforte, A. J., M. Oliver, M. J. Gonzalo, J. M. Alvarez, R. Dolcet-Sanjuan, and P. Arus. 2004. Identification of quantitative trait loci involved in fruit quality traits in melon (Cucumis melo L.). Theor. Appl. Genet. 108:750-758.

Nerson, H., H. S. Paris, and Z. Karchi. 1983. Characteristics of birdnest-type muskmelons. Scientia Hortic. 21:341-352.

Nerson, H. and H. S. Paris. 1987. Effects of plant type and growth regulators on the flowering, fruiting and yield concentrated of melon. Crop Res. 27:19-30.

204 205 Oliver, M., J. Garcia-Mas, M. Cardus, N. Pueyo, A. Lopez-Sese, M. Arroyo, H. Gomez- Paniagua, P. Arus, and M. C. de Vincente. 2001. Construction of a reference linkage map for melon. Genome, 44:836–845.

Paris, H. S., Z. Karchi, H. Nerson, A. Govers, and D. Freudenberg. 1981. A new plant type in Cucumis melo L. Cucurbit Genet. Coop. Rpt. 4:24-26.

Paris, H. S., Z. Karchi, H. Nerson, and Y. Burger. 1982. On the compact appearance of birdnest type muskmelons. HortScience 17:476.

Paris, H. S., H. Nerson, and Z. Karchi. 1984. Genetics of internode length in melons. J. Hered. 75:403-406.

Paris, H. S., T. G. M. McCollum, H. Nerson, D. J. Cantliffe, and Z. Karchi. 1985. Breeding for concentrated-yield muskmelons. J. Hort. Sci. 60:335-339.

Pitrat, M. 1984. Linkages studies in muskmelon. Cucurbit Genet. Coop. Rpt. 7:51-63.

Pitrat, M. 1991. Linkage groups in Cucumis melo L. J. Hered. 82:406–411.

Pitrat, M. 1994. Linkage groups in Cucumis melo L. Cucurbit Genet. Coop. Rpt. 17:148-149.

Perin, C., L. S Hagen, N. Giovinazzo, D. Besombes, C. Dogimont, M. Pitrat. 2002a. Genetic control of fruit shape acts prior to anthesis in melon (Cucumis melo L.). Mol. Genet. Genom. 266:933–941.

Perin, C., M. Gomez-Jimenez, L. Hagen, C. Dogimont, J. C. Pech, A. Latche, M. Pitrat, and J. M. Lelievre. 2002b. Molecular and genetic characterization of a non-climacteric phenotype in melon reveals two loci conferring altered ethylene response in fruit. Plant Physiol. 129:300–309.

Perin, C., L. S. Hagen, V. de Conto, N. Katzir, Y. Danin-Poleg, V. Portnoy, S. Baudracco- Arnas, J. Chadoeuf, C. Dogimont, and M. Pitrat. 2002c. A reference map of Cucumis melo based on two recombinant inbred line populations. Theor. Appl. Genet.104:1017–1034.

Poole, C. F. and P. C. Grimball. 1939. Inheritance of new sex forms in Cucumis melo L. J. Hered. 30:21-25

Prusinkiewicz, P. and J. Haran. 1989. Lindenmayer systems, fractals, and plants. Springer- Verlag. New York.

Prusinkiewicz, P. and A. Lindenmayer. 1990. The algorithmic beauty of plants. Springer- Verlag. New York.

Quijada, P. A., I. J. Maureira, and T. C. Osborn. 2004. Confirmation of QTL controlling seed yield in spring canola (Brassica napus L.) hybrids. Mol. Breed. 13:193-200.

205 206

Rosa, J. T. 1928. Inheritance of flower types in Cucumis and Citrullus. Hilgardia 3: 333-350.

Rosa, J. T. 1924. Fruiting habit and pollination of cantaloupe. Proc. Amer. Soc. Hort. Sci. 21:51-57.

Rowe, P. R. 1969. The genetics of sex expression and fruit shape, staminate flower induction, and F1 hybrid feasibility of gynoecious muskmelon. Ph.D. Diss., Michigan State University.

SAS Institute. 1999. SAS version 8.02 for windows. SAS Institute Inc. Cary, NY.

Santos, C. A. F. and P. W. Simon. 2002b. QTL analyses reveal clustered loci for accumulation of major provitamin A carotenes and lycopene in carrot roots. Mol. Genet. Genom. 268:122-129.

Septiningsih, E. M., J. Prasetiyono, E. Lubis, T. H. Tai, T. Tjubaryat, S. Moeljopawiro, and S. R. McCouch. 2003. Identification of quantitative trait loci for yield components in an advanced backcross population derived from the Oryza sativa variety IR64 and the wild relative O-rufipogon. Theor. Appl. Genet. 107:1419-1432.

Silberstein, L. I. Kovalski, Y. Brotman, C. Perin, C. Dogimont, M. Pitrat, J. Klingler, G. Thompson, V. Portnoy, N. Katzir, and R. Perl-Treves. 2003. Linkage map of Cucumis melo including phenotypic traits and sequence-characterized genes. Genome 46:761-773.

Smith, A. R. 1984. Plants, fractals and formal languages. Comp. Graph. 18:1-10.

Staub, J. E. 2001. Inheritance of RAPD markers in melon (Cucumis melo L.). Cucurbit Genet. Coop. Rpt. 24:29-32.

Staub, J. E., J. E. Zalapa, M. K. Paris, and J. McCreight. 2004. Selection for lateral branch number in melon (Cucumis melo L.). p. 381-388. In: Lebeda, A., H.S. Paris (eds.). Proc. Cucurbitaceae 2004: The 8th Eucarpia meeting on cucurbit genetic and breeding. Olomuc, Czech Republic, July 12-17, 2004. Publisher, Palacky University in Olomuc, Czech Republic.

Sun, Z. Inheritance and molecular mapping of parthernocarphy in cucumber (Cucumis sativus L.). Ph.D. Diss. University of Wisconsin at Madison.

Taha, M., K. Omara, and A. El Jack. 2003. Correlation among growth, yield, and quality characters in Cucumis melo L. Cucurbit Genet. Coop. Rpt. 26:9-11.

Utz, H. F., A. E. Melchinger, and C. C. Schon. 2000. Bias and sampling error of the estimated proportion of genotypic variance explained by quantitative trait loci determined from experimental data in maize using cross validation and validation with independent samples. Genetics 154:1839-1849.

206 207 UWEX. 2001. Commercial vegetable production in Wisconsin. University of Wisconsin- Extension. Cooperative Extension Publishing, Madison, WI.

Van Ooijen, J.W. and R.E. Voorrips. 2001. JoinMap® Version3.0, software for the calculation of genetic linkage maps. Plant research international, Wageningen, the Netherlands.

Vos, P., R. Hogers, M. Bleeker, M. Reijans, T. van de Lee, M. Hornes, A. Frijters, J. Pot, J. Peleman, M. Kuiper, and M. Zabeau. 1995. AFLP: a new technique for DNA fingerprinting. Nucleic Acids Res. 23: 4407-4414.

Vuylsteke, M., R. Mank, R. Antonise, E. Bastiaans, M. L. Senior, C. W. Stuber, A. E. Melchinger, T. Lubberstedt, X. C. Xia, P. Stam, M. Zabeau, and M. Kuiper. 1999. Two high- density AFLP linkage maps of Zea mays L.: analysis of distribution of AFLP markers. Theor. Appl. Genet. 99:921-935.

Wall, J. R. 1967. Correlated inheritance of sex expression and fruit shape in Cucumis. Euphytica 16:1999-208.

Wang, Y. H., C. E. Thomas, and R. A. Dean. 1997. A genetic map of melon (Cucumis melo L.) based on amplified fragment length polymorphism (AFLP) markers. Theor. Appl. Genet. 95:791-798.

Wang S., C. J. Basten, and Z. B. Zeng. 2001-2004. Windows QTL Cartographer 2.0. Department of Statistics, North Carolina State University, Raleigh, NC. (http://statgen.ncsu.edu/qtlcart/WQTLCart.htm).

Yan, W. and I. Rajcan. 2003. Prediction of cultivar performance based on single- versus multiple-year tests in soybean. Crop Sci. 43:549–555.

Zalapa, J. E., J. E. Staub, and J. McCreight. 2004. Genetic analysis of branching in melon (Cucumis melo L.). p. 373-380. In: Lebeda, A., H.S. Paris (eds.). Proc. Cucurbitaceae 2004: The 8th Eucarpia meeting on cucurbit genetic and breeding. Olomuc, Czech Republic, July 12-17, 2004. Publisher, Palacky University in Olomuc, Czech Republic.

Zeng, Z. B. 1993. Theoretical basis of separation of multiple linked gene effects on mapping quantitative trait loci. Proc. Natl. Acad. Sci. USA 90:10972-10976.

Zeng, Z. B. 1994. Precision mapping of quantitative trait loci. Genetics 136:1457-1468.

Zhang, Q., A. C. Gabert, and J. R. Baggett. 1992. Parents and mating systems affect the transfer of gynoecious flowering to Chinese monoecious cucumbers. J. Amer. Soc. Hort. Sci. 117:515–517.