An SNP-based saturated genetic map and QTL analysis of fruit-related traits in Zucchini using Genotyping-by-sequencing
© The Author(s). 2017
Received: 10 September 2016
Accepted: 19 December 2016
Published: 18 January 2017
Cucurbita pepo is a cucurbit with growing economic importance worldwide. Zucchini morphotype is the most important within this highly variable species. Recently, transcriptome and Simple Sequence Repeat (SSR)- and Single Nucleotide Polymorphism (SNP)-based medium density maps have been reported, however further genomic tools are needed for efficient molecular breeding in the species. Our objective is to combine currently available complete transcriptomes and the Zucchini genome sequence with high throughput genotyping methods, mapping population development and extensive phenotyping to facilitate the advance of genomic research in this species.
We report the Genotyping-by-sequencing analysis of a RIL population developed from the inter subspecific cross Zucchini x Scallop (ssp. pepo x ssp. ovifera). Several thousands of SNP markers were identified and genotyped, followed by the construction of a high-density linkage map based on 7,718 SNPs (average of 386 markers/linkage group) covering 2,817.6 cM of the whole genome, which is a great improvement with respect to previous maps. A QTL analysis was performed using phenotypic data obtained from the RIL population from three environments. In total, 48 consistent QTLs for vine, flowering and fruit quality traits were detected on the basis of a multiple-environment analysis, distributed in 33 independent positions in 15 LGs, and each QTL explained 1.5–62.9% of the phenotypic variance. Eight major QTLs, which could explain greater than 20% of the phenotypic variation were detected and the underlying candidate genes identified.
Here we report the first SNP saturated map in the species, anchored to the physical map. Additionally, several consistent QTLs related to early flowering, fruit shape and length, and rind and flesh color are reported as well as candidate genes for them. This information will enhance molecular breeding in C. pepo and will assist the gene cloning underlying the studied QTLs, helping to reveal the genetic basis of the studied processes in squash.
KeywordsCucurbita pepo RIL GBS Cartography Phenotyping Candidate genes
Cucurbita pepo L. is an economically important species of the Cucurbitaceae family cultivated worldwide, with more than 24 million tons produced in 2013 and nearly 1.8 million ha cultivated . It is particularly important in Asian, American and Mediterranean countries, being Mexico and Spain the main worldwide exporters. Like other cucurbits, C. pepo has become a model to study sex expression, fruit set and development, and parthenocarphy [2, 3].
Taxonomically, the species is divided into three subspecies, C. pepo ssp. pepo L., C. pepo ssp. ovifera (L.) Decker (also known as ssp. texana (Scheele) Filov), both of them including cultivated varieties, and C. pepo ssp. fraterna (L.H. Bailey) Lira, Andres & Nee that is considered as a true wild subspecies [4, 5]. The domestication occurred at least twice in Southern USA and Northern Mexico, where the cultivar diversification was initiated. An additional diversification process occurred after the European contact with the New World and the subsequent migration mainly to Mediterranean countries. Nowadays, this species displays a high variability for many agronomic traits, such as fruit shape and color, flowering habit, leaf morphology, etc. [5, 6].
Cultivars are classified in eight horticultural groups (ssp. pepo: Pumpkin, Vegetable Marrow, Cocozelle and Zucchini, and ssp. ovifera: Scallop, Acorn, Crookneck, and Straightneck). The “Zucchini” group rank among the highest-valued vegetables worldwide . Cultivars from Zucchini, Vegetable Marrow and Cocozelle groups, all of them producing elongated fruits, are considered as modern cultivars being newly developed in Europe, whereas the round and flattened Pumpkins and Scallops are ancient groups developed after domestication in North America .
Despite the agricultural and biological interest of this species, knowledge of its genetics and genome has been very limited in comparison with other cucurbits [9–11]. Recently, we produced the first transcriptome of the species, from root, leaves, and flower tissues, by using the 454 sequencing technology  that was later significantly improved with Illumina technology by sequencing cDNA from additional tissues (shoot apices, floral buds, and pre-harvest and postharvest fruit subjected to ethylene, methylcyclopropene and cold treatments). The C. pepo transcriptome v3 is available at the Cucurbigene website . Genes were annotated and classified in different biological functions. Some of them have been recently used to study biological processes in Cucurbita [2, 14].
The transcriptome sequencing was focused on two varieties with contrasting phenotypes, representing the two C. pepo main subspecies, the inbreeding line ‘MU-CU-16’, belonging to the Zucchini morphotype (C. pepo ssp. pepo), the main summer squash sold in European markets, and the inbreeding line ‘UPV-196’ of the Scallop morphotype (ssp. ovifera). These genotypes also represent different domestication and diversification steps, Scallop types were already selected by Native Americans, whereas elongated Zucchini were selected in Italy after the introduction of this species in Europe . Recently, other transcriptomic studies have been carried out with specific purposes, for instance, to identify genes involved in aphid infestation , or to develop markers in Pumpkin types .
Dense genetic maps are necessary tools for efficient molecular breeding. In the past decades, the linkage maps of the Cucurbita genus were constructed using populations derived from both inter (C. pepo x C. moschata) and intra-specific crosses (C. pepo ssp. pepo x ssp. pepo, and C. pepo ssp. pepo x ssp. ovifera). These maps were first composed of dominant markers (Random Amplified Polymorphic DNA (RAPD) and Amplified Fragment Length Polymorphisms (AFLP)) [18–20], and later completed with SSRs [21, 22]. The two genotypes, Zucchini and Scallop, used to generate the C. pepo transcriptome were also selected previously as parents of an F2 mapping population that was employed to construct the first SNP-based genetic map of the species and to map several QTLs (Quantitative Trait Loci) involved in plant, flowering and fruit traits .
The SNPs located in the map by Esteras et al.  were selected among those identified in silico by mining the transcriptomic sequences of the F2 parents (‘MU-CU-16’ and ‘UPV-196’), and were validated using a Golden-Gate genotyping platform. Despite this map produced valuable information, its marker density was only moderate (6.02 cM/marker). New methods integrating simultaneously SNP discovery and genotyping such as Genotyping-by-sequencing (GBS) [24, 25] can be applied to rapidly develop high-density genetic maps.
The aim of this work is to generate a high-density genetic map using several thousands of SNPs obtained by the GBS analysis of a new Recombinant Inbred Line population (RIL), developed through single seed descent from the previous Zucchini x Scallop F2 population . RIL populations are more adequate for genetic mapping as a higher number of recombinations are produced, improving the mapping resolution, and they can be replicated by seed, making easy replicated trials that facilitates a better estimation of QTL effects . Consequently, we also investigated the genetic control of economically important traits as vine, flowering and fruit quality traits, by QTL analysis, taking advantage of the new high-density map and of the first draft of the C. pepo genome available at the Cucurbigene website . The results presented herein will help to establish a molecular breeding system in this species.
Generation of the RIL population
Two genotypes of C. pepo were used as parentals to produce the intra-specific RIL mapping population used in this study, belonging to different subspecies, ‘MU-CU-16’ is a Zucchini type of the subspecies pepo and ‘UPV-196’ is a Scallop type of the subspecies ovifera. The two parents present contrasting phenotypes for vine, flowering and fruit traits detailed in . F1 plants produced from the Zucchini x Scallop cross were selfed to generate the F2 population used to construct the first SNP-based map in C. pepo . F2 individual plants were selfed until the F8 generation by single seed descent. A final set of 120 F8 RILs was obtained.
DNA was isolated from young leaves of plants of each of the 120 RILs. Additionally, three replicated samples of parentals and the F1 generation and two independent DNA extractions of two randomly selected RIL families were included as controls. DNA extraction was carried out using DNeasy Plant Mini Kit (Qiagen, Hilden, Germany). DNA concentrations were measured with Nanodrop ND-1000 Spectrophotometer v.3.5 to select samples with at least 50 ng/μl. Finally, 131 samples with high-quality DNA were selected for sequencing. Samples were sent for genotyping to the Genomic Diversity Facility at Cornell University (Ithaca, New York, USA). A minimum of 500 ng of DNA were used for SNP genotyping.
A Genotyping-by-sequencing approach was used for SNP discovery between the parents and among the RILs as described by Elshire et al. . The GBS libraries from all samples were prepared using ApeKI endonuclease (recognition site: G/CWGC) and sequenced using the Illumina HiSeq 2000 platform (Illumina Inc, San Diego, CA, USA). GBS libraries were constructed including the parents and F1 (three replicates each) and 122 RIL samples. GBS sequencing reads were de-multiplexed according to the sample barcodes and adapter sequences were removed using GBS barcode splitter . Reads were trimmed by base Phred quality (Q score < 25) and reads shorter than 30 base pairs were discarded before mapping and SNP calling.
The filtered, high-quality sequences from each sample were aligned to the last version of the C. pepo genome v.3.2  using Bowtie 2 with default parameters . SNP calling was performed using Freebayes . A minimum mapping quality of 30, minimum base quality of 20 and minimum coverage of 5 was required. Resulting SNPs were additionally filtered discarding those with more than 70% of missing data, no biallelic, with a Minimum Allele Frequency < 10%, or with heterozygosity >70%. Genotypes with a quality lower than 10 were also discarded.
Phenotyping of the RIL population
The seeds of 120 F8 RILs were germinated in Petri dishes and transplanted to pots (in glasshouses) and to soil (under tunnel) at 2 weeks after germination in three independent assays. The first assay was performed from February to July 2014 (assay Paip2014) at the tunnel facilities of CAJAMAR (Paiporta, Valencia, Spain). Three plants per RIL were phenotyped. DNA for GBS analysis was obtained from this trial. The other two assays were conducted in 2015, at the same tunnel facilities (Paip2015, from February to July) and in the glasshouse facilities at the Polytechnic University of Valencia (UPV) (Valencia, Spain, from May to October, UPV2015). In these two assays, also three sister plants were phenotyped per RIL with a fully randomized experimental design.
In the three assays we measured traits related to vine growth, plant morphology, flowering and fruit traits. Forty-three traits were measured for each single plant (Additional file 1). Vine traits were related to plant length (growth habit, plant length, and number of nodes of the plants at the end of the assay), branching intensity, and leaf traits (spines in the leaf petiole, leaf incision, and occurrence of silver leaf); and flowering traits were related to the flowering time (first node with male/female flower, and days from transplanting to the development of the first male/female flower).
Each plant was selfed and two fruits per plant were analyzed. One of them at immature stage, 7 days after pollination, which corresponds to the commercial stage of summer squashes. The second fruit was analyzed at physiological maturity (ranging from 30 to 60 days after pollination). Traits measured at both physiological states were immature/mature peduncle length, fruit size and shape (fruit length, width, shape, weight, number of locules and ribbing), flesh firmness, rind and flesh color, and sugar content and acidity. More details about all measured traits are included in Additional file 1.
Data from the assays performed in the three locations were used to calculate pairwise genetic correlations between locations as r x,y = covariance x,y/√(variance x * variance y), where x and y represented two different locations .
Genetic map construction and QTL detection
A genetic map was constructed using R packages R/qtl  and ASMap . ASMap package implements the MSTmap algorithm , which is an extremely fast algorithm for linkage map clustering and ordering of thousands of markers. SNPs were coded as homozygotes similar to one parent (A), to the other (B) or heterozygotes (H) using custom scripts. Polymorphic loci that were heterozygous in any of the parents, markers with more than 10% of missing data or duplicated markers (markers with the same genotype for all individuals) were discarded. To remove possible genotyping errors, we used our own implementation of the SMOOTH algorithm . This method corrects the genotype of an individual based on neighboring markers. mstmap function from ASMap package was used to cluster and order markers and quickEst to estimate genetic map distances using Kosambi map function . To detect segregation distortion, Chi-square (χ2) tests were computed for each SNP using R/qtl function geno.table and p-values were corrected for multiple testing using Benjamini and Yekutieli correction . Highly distorted and unlinked markers were excluded from analysis. Mapchart 2.2  was used to visualize a constructed map for each linkage group (LG). The new map was compared with the previous C. pepo 384-SNP map developed with the F2 population derived from the same Zucchini x Scallop cross . This set of SNPs were located in the C. pepo genome v.3.2 using BLAST with their flanking sequences in order to obtain an equivalence between Esteras’ genetic map and current genome version. Linkage groups were named according to the RIL map generated in the current study.
Once the genetic map was established, SNPs showing segregation distortion were located in the physical map together with the mapped SNPs to identify genomic regions with genetic distortion.
QTL analysis for each trait was performed by Composite Interval Mapping (CIM) using the R/qtl function cim with a scan window size of 20 cM and 20 background marker loci as QTL cofactors. A multi environment search of QTLs was performed using the data from the three assays. Environmental effects and Genotype x Environment (G x E) interactions were estimated for each trait using a two factor Analysis of Variance (ANOVA), with all the phenotypic data. Also an additional QTL analysis was performed per environment, using data of each assay separately. Logarithm of odds (LOD) threshold for a Type I error P < 0.05 and P < 0.01 value was obtained based on a permutation test (1000 permutations were run per trait). LOD support interval was calculated using R/qtl lodint function using a 1.5 LOD units drop. The additive QTL effect (a) and the proportion of phenotypic variance explained by QTL (R2) were estimated at the highest QTL peaks using R/qtl function fitqtl. QTLs exceeding the threshold value (p < 0.01) in this analysis were considered significant.
Results and discussion
Sequence data and SNP discovery
A total of 242.4 million cleaned reads with a total of 21.7 Gb were generated for the parents, F1 and the 122 RIL samples. The number of reads obtained varied from 0.9 million to 4.6 million with an average of 1.85 million reads per line. The genome of C. pepo v3.2 has a total assembled size of 263,500,453 bp (with 909 large scaffolds > = 10 Kb). All the cleaned reads represent an average percentage of covered genome with a read depth > 1 and > 20 of 3.0% and 0.5%, respectively (Additional file 2). Sequences have been submitted to the Sequence Read Archive (SRA) of the NCBI (SRR4299463-SRR4299615, BioPoject PRJNA344022).
The sequences obtained were filtered and used for SNP identification. A 93.9% of the cleaned reads were mapped to the C. pepo genome and 62,617 SNPs were identified after the SNP calling with Freebayes. After excluding SNPs that were monomorphic in the RIL population, those non biallelic, with more than 70% of missing data, with heterozygosity >70% or with Minimum Allele Frequency (MAF) < 10%, 26,430 SNPs remained. The SNPs identified were again filtered to remove heterozygous SNPs in parents.
The number of SNPs identified in this population is higher than the number identified in a recent GBS analysis performed using an F2 population derived from the cross between two accessions of the closely related species Cucurbita maxima . Using the same filters employed in the study by Zhang et al. , that is, selecting SNPs with less than 20% missing data and MAF ≥ 0.2, we identified about eight times more SNPs in our RIL population, 16,222 SNPs in C. pepo RIL population versus 1,881 in C. maxima population. Differences can be explained by the higher variability of the C. pepo species and by the fact that we have crossed two accessions belonging to two different subspecies generated in two independent domestication events .
Construction of genetic map
A genetic map was constructed using genotypic data of the RIL population. After discarding those SNPs with more than 10% of missing data, and those showing a statistically significant deviation from Mendelian segregation, 10,166 SNPs distributed in 178 scaffolds (representing 212,381,440 bp, 80.6% of the genome) remained. We found 3,676 SNPs forming groups of SNPs with the same genotype for all samples. Only one SNP per group was retained. We also removed unlinked markers and SNPs that had different genotypes in the two DNA replicates used as controls. The average degree of heterozygosity existing in this F8 RIL population was 1.47% (ranging from 0.013 to 3.72%).
Genetic map of a RIL population of C. pepo
Average spacing (cM)
Maximum spacing (cM)
N° of nucleotides (% of total genome)
N° of anchored scaffolds
C. pepo v3.2. scaffolds
10, 24, 32, 40, 46, 51, 59, 63, 78, 79, 84, 91, 105, 111, 144, 175
1, 41, 55, 62, 76, 99, 128, 140, 162, 168, 169, 208
6, 19, 38, 44, 117, 118, 122, 163, 187, 195, 210
20, 21, 22, 66, 86, 143, 159, 180
12, 18, 48, 71, 121
3, 8, 89, 101
35, 36, 42, 43, 82, 83, 106, 13127
14, 26, 61, 72, 75, 132
13, 54, 64, 77, 130, 146, 161, 197
9, 29, 68
15, 16, 47, 131
30, 31, 45, 58, 65, 74, 96, 103, 120, 186
17, 49, 53, 88, 94, 107, 108, 113, 124, 141, 153
23, 56, 60, 69, 92, 93, 97, 98, 119, 135, 172
28, 30, 34, 80, 85, 104, 129
4, 67, 70, 78, 100, 152, 200, 206
7, 52, 81, 110, 115, 148
This new map significantly improves the previously reported C. pepo map constructed with the F2 population in the earlier study by Esteras et al. , which included 315 markers covering 1,740.8 cM, with an average distance between markers of 6.02 cM and a maximum gap of 30.3 cM. The sequences of these markers were mapped to the C. pepo genome to compare both maps. It was possible to associate most of the linkage groups established in the F2 map, with unique LG of the new high density genetic map (Fig. 1). The RIL map enabled merging former LGs 19 and 21, and 22 and 12 (corresponding to new LG 2 and 7 respectively). Also current LG 18 and 20 corresponded with the former LG 3. Therefore, the comparison of both maps revealed 20 linkage groups that corresponded to the 20 chromosomes of C. pepo.
The map length is similar to that reported for C. maxima, 2,566.8 cM , with a much higher marker density, 385.9 versus 22.9 marker per LG, an average of 0.4 versus 5.6 cM between successive markers, and fewer genetic gaps, making the current map the most saturated genetic map of the Cucurbita genus to date.
SNPs with statistically significant distorted segregation that were discarded for map construction, were located in the genome (Additional file 3b). In some regions, distorted SNPs were interspersed with non-distorted SNPs, so the observed distortion was not likely due to genetic reasons, but to artefacts of the GBS analysis or complex genomic causes (i.e., gene duplication or deletion). However, in other regions, blocks of continuous distorted SNPs were observed. In such cases, a real genetic distortion was assumed (Additional file 3c). These regions were mainly located in the distal region of LG 19 (CP32_scaffold000005_127543-2532610 Scallop alleles overrepresented) and of LG 21 and LG 20 (CP32_scaffold000007_32640-4220403 and CP32_scaffold000027 11033-2401349, Zucchini alleles overrepresented). This distortion in the distal region of LG 20 could explain why this LG could not be merged with LG 18 in the RILs map (Fig. 1). Other regions with distorted segregation were for example in LG 16 (28.2–51.4 cM; CP32_scaffold000028_577-1064181), LG 12 (91.9–111.1 cM, scaffold000045_87006-1620317), LG 1 (127.3–129.5 cM, scaffold000084_267107-735527) and LG 4 (24.5 cM, scaffold000086_313524-580307), with Scallop alleles overrepresented, and in LG 15 (9.2 cM, scaffold000060_271409-477442), with Zucchini alleles overrepresented. Also some scaffolds that could not be anchored to the genetic map showed distorted segregation skewed towards Zucchini and towards Scallop alleles, respectively. Some of these regions were also observed in the former F2 map, mainly in the previous LG 2 and LG 5 (current LG 1 and 21).
Different functions were associated to the genes located in the distorted regions. Some were directly related to the flowering process (Protein UNUSUAL FLORAL ORGANS: CP32_scaffold000007_1554474, squamosa promoter binding protein-like: CP32_scaffold000045_1030767 and CP32_scaffold000084_557489, Flowering time control protein FPA: CP32_scaffold000045_1196335) [39–41]. Others are transcription factors involved in plant growth and development (Scarecrow-like transcription factor PAT1: CP32_scaffold000050_1278397, TCP family transcription factor: CP32_scaffold000084_653160), in the embryogenesis process (embryo defective 2170: CP32_scaffold000028_353221, Homeobox protein knotted-1-like 7: CP32_scaffold000086_568011) [42, 43] or genes related to hormone metabolism (ethylene or auxin related) (Additional file 3c). Scallop and Zucchini alleles were overrepresented in different regions, suggesting that the alleles in this region may be subjected to gametic or zygotic selection and/or related to preferential germination or better seedling viability. Some of these unigenes may be the cause of the segregation distortion, but it could also be the result of linkage to other genes.
QTLs detected for vine, flowering, plant and fruit traits
Genetic position (cM)
Days to female flowering
Days to female flowering
Immature Fruit shape
Immature fruit shape
Immature Fruit length
Immatute fruit length
Immature fruit length
Immature Fruit width
Mature Fruit shape
Mature fruit shape
Mature fruit shape
Mature Fruit length
Mature fruit length
Mature fruit length
Mature fruit length
Mature Fruit width
Mature fruit width
Immature fruit ribbing
Mature fruit ribbing
Matre fruit ribbing
Immature peduncle length
Immature peduncle length
Mature peduncle length
Immature rind color, L parameter
0.00E + 00
Immature rind color, L parameter
Immature rind color, L parameter
Immature rind color, b parameter
Immature rind color, b parameter
Immature rind color, b parameter
Immature rind color, a parameter
Immature rind color, a parameter
Mature rind color, L parameter
0.00E + 00
Mature rind color, L parameter
Mature rind color, L parameter
Mature rind color, b parameter
Mature rind color, b parameter
Mature rind color, a parameter
Immature flesh color, b parameter
Immature flesh color, a parameter
0.00E + 00
Immature flesh color, a parameter
Mature flesh color, b parameter
0.00E + 00
Mature flesh color, a parameter
Mature flesh color, a parameter
Mature flesh color, a parameter
No significant QTLs were found for vine size and architecture despite RIL parents, Zucchini and Scallop, differed in growth habit (bushy versus intermediate), branching intensity (non-branched versus branched), and plant length and number of nodes (an average from 78 to 120 versus 210 to 277 cm, and from 5 to 70 versus 73 to 90 nodes, in the three environments for Zucchini and Scallop respectively).
Major QTLs were identified for leaf traits, such as leaf blade incision and the occurrence of silver leaf (Li_10 and Sl_12) (Table 2 and Additional file 4), both traits related to photosynthesis rate. Zucchini plants developed deeply incised leaves whereas Scallop plants had weak incisions (Li scored as 4 versus 1 respectively in all environments). Large genetic correlations between locations where found for these two traits, r x, y ranging from 0.66 to 0.77 (Additional file 4) indicating that the norm of reaction for each genotype was similar in the three environments.
Silvered leaves exhibit reduced photosynthetic ability, but this trait also seems to have a favorable effect on protection against aphids or plant desiccation, as silvery leaves reflect more light than non- silvery leaves . A further study of the genes annotated in the corresponding QTL intervals (Additional file 6) is of interest to identify candidates involved in the variation of this trait and to manage it in breeding programs.
Flowering time related traits
Cucurbits have become model species for the study of plant sex determination and some genes involved in sex expression (dioecy, monoecy, andromonoecy and gynoecy) have been characterized in melon, cucumber and squash [14, 50–55]. Most of them are enzymes involved in ethylene biosynthesis, signaling and regulation. The Cucurbita orthologs of some of the cloned genes (CmACS11, CmACS7, CsACS2, CSACS1g and CmWIP1 of melon and cucumber) are located in LG 13, LG 14, LG 18, LG 10, and LG 17 (CP32_ scaffold000017_63557, CP32_scaffold000011_561409; CP32_scaffold00025_1079779; CP32_ scaffold000009_993755; CP32_ scaffold000004_4527055). Other genes, such as CTR1 and CTR2, that confer reduced ethylene sensitivity and have been reported to be involved in the male/female ratio in C. pepo  are located in LG 3 and LG 6 (CP32_ scaffold000038_689227 and CP32_ scaffold000008_2476160). No significant QTLs involved in the variation of the flowering traits analyzed in this study colocalize with any of these regions (Additional file 4). This result is not unexpected as the Zucchini and Scallop accessions do not differ in sex expression, being both monoecious. In fact, sex expression is less variable in Cucurbita than in Cucumis crops, cucumber and melon.
Early flowering, however, is a highly variable and economically important agronomic trait related to early yield in C. pepo. It is affected by genetic, environmental and hormonal factors [57, 58]. Zucchini and Scallop do differ in flowering time, mainly in the days to the development of the first male and female flower, being the Scallop parental more late-flowering than Zucchini squash (average DMaF 18 to 23.5 versus 21 to 24.5 days and DFeF 18 to 30 versus 31.5 to 42 for Zucchini and Scallop in the three environments, respectively). Genetic correlations between locations for this trait were positive and significant, although moderate (r x, y > 0.28) (Additional file 4). The analysis of the RIL population suggests the existence of at least two genomic regions controlling flowering time. We found a QTL (R2 = 7.9%) involved in the earliness of female flowers in LG 12 (DFeF_12, 33.1 cM, CP32_scaffold000074_621895-CP32_scaffold000096_181501) (Table 2, Additional file 4). ANOVA results also indicate a significant effect of the environment and a lack of G X E interaction in this locus (Table 2). The RILs homozygous for the Zucchini alleles developed the first female flower in all environments between 3 and 8 days before than those homozygous for the Scallop allele (average DFeF 34.2 versus 39.7 days) (Additional file 5). One additional minor QTL involved in the variation of the same trait was found in LG 9 (R2 < 5%), DFeF_9 (116 cM, CP32_scaffold000013_960688-CP32_scaffold000013_1308585) (Table 2 and Additional file 4), with significant E and G x E effects. Significant differences between the RILs with the Zucchini versus Scallop genotypes in this region were found in two environments, with an advance of the female flowering from 2 to 6 days (average DFeF 34.9 versus 37.4 days) (Additional file 5).
Some candidate genes are found in these regions (Additional file 6), opening new possibilities for the study of the genetics of this poorly studied trait. For example, two MADS-box genes are annotated in the DFeF_12 region (CP32_ scaffold000074_189252-192320 and 193342-199503) that are most similar to the Momordica charantia AGAMOUS LIKE6-like protein (AG6) and to the MADS-box protein SOC1-like from C. sativus. The AGL6 gene acts as a floral promoter in Arabidopsis through the control of the transcription of key regulators of flowering time (the FLOWERING LOCUS C (FLC), the main flowering switch gene in Arabidopsis, and the FLOWERING LOCUS T (FT)). The overexpression of this gene results in a late-flowering phenotype . Also the overexpression of SOC1-like stimulate flowering in different species . In this region is also located a TCP transcription factor (CP32_ scaffold000074_159157-160182, best nr hit transcription factor TCP9 of C. melo). The TCP gene family plays important roles in regulating diverse processes, including phytohormone biosynthesis and signal transduction, branching and flower development . A gene of this family was also annotated in the distorted region of LG 1 described above (Additional file 3c).
Variation in flowering time has been less studied than sex expression in cucurbits and little is known about the underlying genetic mechanism. In a recent study conducted in cucumber, a candidate gene for early flowering was identified (Csa1G651710), which is a homolog of the Arabidopsis LOCUS T . Our results suggest that the regulation of the FT gene is also a main mechanism underlying the variation of the flowering time in C. pepo. The C. pepo ortholog of the Csa1G651710 is located in the scaffold150 (CP32_scaffold000150_132214-134774) that could not be mapped to any of the C. pepo linkage groups. This scaffold showed a high degree of distorted segregation towards the Zucchini alleles (Additional file 3c), which is consistent with the idea that Scallop alleles in this locus have resulted in late flowering affecting the reproduction of the carrier RILs during the selfing process. It remains to be studied if the presence of Zucchini regions in DFeF_12 results in a change of FT expression associated to the early flowering genotypes.
Additionally, three genes are located in the region of the DFeF_9, that can be associated to the flowering process, one annotated as WUSCHEL-related homeobox (WOX) (CP32_ scaffold000013_1016547-1018778, Best hit WUSCHEL-related homeobox of Cucumis melo) and a second gene as an auxin response factor 4 (CP32_ scaffold000013_1041004-1045906). WOX genes are a large group of transcription factors essential in maintaining shoot apical meristem, some of which play important roles in the regulation of floral patterning. Some of these processes are conducted through the regulation of auxin transport [63, 64]. The third candidate in this region is an ethylene-responsive transcription factor (ERF4) (CP32_scaffold000013_1092413-1092817) as flowering is also associated to ethylene metabolism. Further research is necessary to determine whether flowering time traits co-segregate with variation in these genes.
None of these QTLs colocalize with the major QTL in LG 3 controlling several flowering traits (days to flowering, node to the first flower, etc.) detected using the F2 population of the same cross and the previous map by Esteras et al. . Former LG 3 corresponds to LG 18 and LG 20 in the current map (Fig. 1). The SNPs flanking the flowering QTL in the F2 map (C006328, C001057 and C003831) were located in CP32_scaffold000027 (507871 and 2031514) and CP32_scaffold000025 (1811879), the first and second ones anchored in one end of the LG 20 and the last in another end of the LG 18. The CP32_scaffold000027 presents a high percentage of distorted markers (Additional file 3c), thus as described before we were not able to merge this two LG into one. Therefore, likely the lack of markers in this region is the reason why this main QTL detected in the F2 was not detected in the RILs population. In this region are two ETHYLENE INSENSITIVE3 (EIN3) genes and one ethylene-responsive transcription factor (ERF) annotated (CP32_scaffold000025-1811503 and 2037348; CP32_scaffold000027-1697493-1702248) encoding transcription factors that represent downstream components of ethylene signaling, also reported to be involved in flowering .
Squash fruit morphology is related to different traits: fruit weight, fruit shape, fruit length and width, number of locules, and ribbing intensity. Zucchini and Scallop immature and mature fruits did not significantly differ in fruit weight, but they did differ in fruit shape (IFSh and MFSh scored as 6, elongated, versus 1, discoidal, respectively). Fruit shape differences were mainly due to differences in fruit length (IFLe from 16.7 to 23.7 cm versus 4.7 to 7.5 cm, and MFLe from 37.8 to 38.7 cm versus 6.9 to 9.8 cm, respectively for Zucchini and Scallop in the three environments).
Genetic correlations between locations were very high for some traits related to immature and mature fruit shape (r x,y ranging from 0.65 to 0.89 for IFSh, IFLe, MFSh, MFLe), and moderate for some others (r x, y ranging from 0.33 to 0.65 for IFWi, IFRib, MFWi, and MFRib) (Additional file 4).
Two additional minor QTLs affecting immature fruit shape and length, IFSh_12 (R2 = 6.7%, 25.0 cM, CP32_scaffold000065_760668-CP32_scaffold000074_729362) that colocalized in LG 12 with minor QTLs affecting immature and mature fruit length and width (IFLe_12, MFLe_12 and MFWi_12) (R2 = 7.6, 6.6 and 7.4%, 24.2, 19.3 and 24.9 cM), and IFLe_15 (R2 = 6.7%, 34.7 cM, CP32_scaffold000056_543412-CP32_scaffold000056_920404) were identified (Table 2, Additional file 4). In all cases Zucchini alleles increased fruit length, but the effects of these QTLs were much lower than that of QTLs in LG 3 and significant differences were found only in some environments (Additional file 5).
Also four additional regions in LG 4 (39.4 cM, CP32_scaffold000159_92504-CP32_scaffold000022_375710), LG 5 (27.9 cM, CP32_scaffold000018_362002-CP32_scaffold000018_549964), LG 6 (19.7 cM, CP32_scaffold000003_3022364-CP32_scaffold000003_3087204), and LG 9 (119.3 cM, CP32_scaffold000013_890110-CP32_scaffold000013_959962) affected mature fruit shape and length, MFSh_4, MFSh_5, MFLe_6 and MFLe_9 (R2 = 3.4, 3.0, 3.6 and 6.2%) (Table 2, Additional file 4). MFLe_9 was the only QTL in which the Scallop alleles increased fruit length (average MFLe 19.1 versus 22.7 cm for Zucchini and Scallop respectively) (Additional file 5). In these four QTLs the effect was only observed in mature fruits, suggesting that different regions affect fruit shape in the early and late steps of fruit development. Several genes had been previously reported to be related to fruit shape in C. pepo . A dominant gene (Di) was reported associated to the discoidal fruit shape of scallop squash. This gene was suggested to be dominant over spherical or pyriform shapes. A digenic epistatic control has also been reported for summer squash fruit shape. Our results are consistent with the existence of a major gene, that could be the ovate underlying the IFLe_3 QTL, and several minor modifiers.
Peduncle length is also involved in fruit typology. Significant differences were found among parents in the three environments, with shorter peduncles in the Zucchini fruits (IPeLe 2–3 versus 4.3–5.3 cm and MPeLe 1.4–3.6 versus 5.2–9.5 cm). Genetic correlations between assays were moderate for peduncle traits (Additional file 4). Three QTLs were identified controlling immature and mature fruit peduncle length (Table 2 and 3, Additional file 4): IPeLe_10 (R2 = 7.6%, 71.3 cM, CP32_scaffold000009_272548-CP32_scaffold000009_704495), IPeLe_16 (R2 = 3.7% 14.9 cM, CP32_scaffold000030_1135277-CP32_scaffold000030_1337312) and MPeLe_14 (R2 = 3.9%, 29.3 cM, CP32_scaffold000039_1662180-CP32_scaffold000011_1038061). These QTLs have opposite effects of the Zucchini versus Scallop alleles (IPeLe 4.2 versus 5.5 and 5.3 versus 4.4 for IPeLe_10 and 16, respectively and 4.4 versus 5.3 for MFLe_14) (Additional file 5).
Apart from fruit shape, other factors involved in fruit quality have been studied: organoleptic (flesh sugar content, Brix, and acidity, pH), nutritional (several measures of rind and flesh color), and physical (flesh firmness). Zucchini and Scallop parents did not differ in flesh firmness, Brix degree and pH, but clearly differed in fruit color, both of rind and flesh. Color was measured with colorimeter (taking the three parameters of the Hunter scale, L, Lightness, from white, L = 100, to black, L = 0; a, from redness for positive values to greenness for negative values; b, from yellowness for positive values to blueness for negative values). The Zucchini parent develops immature dark green fruits (characterized by low ILRCo values, 24.4 to 28.3, negative IaRCo, −2.6 to −6.8, and, positive IbRCo, 4.3 to 4.6, scores) with light green flesh (characterized by high ILFCo values, 52.9 to 81.3, negative IaFCo, −4.3 to −6.8, and high IbFCo values, 11.1 to 23.8) in the three environments. Immature Scallop fruits have light green rinds (with significantly higher values of ILRCo, 64.7 to 77.3 and IbRCo, 17.7 to 19.1, but similar values of the a parameter) and light green flesh, similar to that of the Zucchini fruits (ILFCo 79.5 to 82.4, IaFCo −4.1 –6.6, and IbFCo 13.9–15.5). Color differences were more significant in mature fruits. Zucchini fruits were dark green (MLRCo 21.2 to 25.6, MaRCo −1.6 to −0.48 and MbRCo 1.2 to 6.0), and the flesh varied from light green to light yellow or orange at physiological maturity (MLFCo 49.8 to 76.6, MaFCo −1.6 to 0.8 and MbFCo 12.9 to 24.4). However, the Scallop fruits remained white, both rind and flesh, at full maturity (with significantly higher rind and flesh lightness, MLRCo 78.8 to 81.9 and MFLCo 78.7 to 80.4, and rind yellowness values, MbRCo 11.4 to 12.5, and significantly lower flesh redness and yellowness, MaFCo −1.3 to −0.62 and MbFCo 9.7 to 13.3). Genetic correlations between environment were very high for the L trait (r x, y >0.75) and from moderate to high for the a and b color parameters (r x, y > 0.45) measured both in fruit rinds and flesh (Additional file 4).
In the LOD peak region of these QTLs, two genes annotated as related to an Arabidopsis APRR2-Like (ARABIDOPSIS PSEUDO RESPONSE REGULATOR2-LIKE gene) (CP32_ scaffold000180_115300-127146 and 130920-135450) (Additional file 6) were found. Genes of this family have been demonstrated to act as fruit-related regulators of pigment accumulation in tomato and pepper . In fact the presence of a stop codon mutation explain color differences between the wild-type and a white-fruited pepper cultivar associated to differences in chlorophyll content. Our results also suggest a similar function of these genes in the Cucurbitaceae family.
Apart from the main effect of ILRCo_4-IbRCo_4/MLRCo-4MbRCo_4, immature rind color seems to be controlled by additional genomic regions. The main ones were in LG 10 and LG 3. The first region affected also flesh color, ILRCo_10, IaRCo_10, IaFCo_10 and IbFCo_10 (R2 = 6.0, 9.7, 28.3 and 15.0%, 99.5, 104.9, 100.4 and 102.9 cM, CP32_scaffold000029_1132025-CP32_scaffold000029_1802506). RILs with Scallop/Zucchini genotype had immature fruits with different greenish and yellowish tones in rind and flesh (ILRCo 67.9 versus 60.5 and IaRCo −8.3 versus −10.4, IaFCo −6.2 versus −4.1 and IbFCo 16.6 versus 13.9 for Zucchini and Scallop, respectively) (Additional file 5). A similar effect was found in LG 3 (IaRCo_3, R2 = 12.1%, 86.1 cM CP32_scaffold000187_88187-CP32_scaffold000187_88366), but significant environment and G x E effect were found in this region (Table 2, Additional file 4). Other less important regions (R2 < 5%) involved in the variation of immature rind color were ILRCo_1, IbRCo_3 and IbRCo_12. These results are consistent with the traditionally proposed genetic control for rind color in squash, with a major gene derived from the Scallop genotype, W (weak rind coloration), complemented by modifiers, which confers a white or cream solid color independently of the genetic background. This gene has been reported to be epistatic to D (Dark stem) derived from Zucchini squash that result in dark stem and dark intermediate-age fruit . The APRR2-like genes underlying ILRCo_4-IbRCo_4/MLRCo-4MbRCo_4 are good candidates to be the W previously described squash gene.
The rind color of mature fruits was more variable than the immature fruit color, as during the ripening process yellow and orange colors develop in some fruits (Fig. 6b). Two QTLs were found involved in the redness (a parameter) variation (MaRCo_4 50.4 cM, CP32_scaffold000022_ 598182-CP32_scaffold000022_1004798) and in the yellowness (b parameter) variation (MbRCo_19, 52.1 cM, CP32_scaffold000005_1580923-CP32_scaffold000005_2422557). The major QTL MaRCo_4 explained most of the variation found in MaRCo (R2 = 18.6%), with the Zucchini alleles resulting in fruits with more orange color in rinds in all environments (MaRCo 0,88 versus −2,6 for Zucchini and Scallop genotypes) (Additional file 5). The QTL MbRCo_19 (R2 = 8.6%) resulted in fruits with rind color variable for the yellowness trait (MbRCo 22.2 versus 16.9 for Zucchini and Scallop genotypes). MbRCo_19 colocalized with the major QTL explaining variation in mature flesh color discussed below. Two additional minor (R2 < 5%) QTLs affecting rind lightness were detected in LG 1 and 2, MLRCo_1 and MLRCo_2 with Zucchini genotypes having darker fruits than Scallops, but with a significant environment and G x E interaction (Additional file 5).
The genetic control of external fruit color has been investigated in melons. Recently, Feder et al.  identified a Kelch domain-containing F-box protein regulating naringenin chalcone accumulation in melon rind producing the change from white to yellow rind. This gene (MELO3C011980, annotated as similar to F-box/kelch-repeat protein At1g23390) colocalizes with QTLs involved in the variation of external color in melons [72, 73]. In C. pepo, we found two genes annotated as F-box/kelch-repeat protein (Additional file 6) in the LOD peak regions of the MaRCo_4 QTL (CP32_ scaffold000022_600093-603383 and 624476-611084, best nr hit F-box/kelch-repeat protein At1g55270-like and At2g44130-like respectively). Also a Zeaxanthin epoxidase (ZEP) gene (CP32_ scaffold000022_750677-751766), an enzyme known to be involved in carotenoid metabolism , was found in that region. Also in the region of the QTL MbRCo_19 is annotated a Phytoene synthase (PSY) enzyme (CP32_scaffold000005_2373613-2377294), known to be involved in the carotenoids biosynthesis (Additional file 6).
Other two minor QTLs (R2 < 5%) involved in the variation of flesh color were also detected, although with significant E and G x E effect (Additional file 5) (MaFCo_10, 37.9 cM, CP32_scaffold000009_1923620-CP32_scaffold000009_2317405, and MaFCo_13, 53.1 cM, CP32_scaffold000017_2743863-CP32_scaffold000108_169208) that can act modulating the effect of the major gene, as it has been also reported in melons [72, 73, 78–80].
A high-quality SNP marker collection has been developed for mapping and construction of the first saturated map in the species, with more than 7,000 markers and anchored to the current version of the C. pepo genome by 145 scaffolds. The improvement in the number of markers per LG and the extensive phenotyping of the RIL population, have enabled the detection of 48 QTLs, most of them stable across three environments.
The availability of the C. pepo genome annotation https://cucurbigene.upv.es  has facilitated the identification of candidate genes underlying most of these QTLs, which will allow the knowledge of the underlying processes that give rise to these phenotypic traits. We can highlight the identification of candidate genes underlying the variation of QTLs that explain more than 30% of the variation found in leaf incision, fruit shape, rind and flesh color, traits of evident economic importance, which can be exploited for searching new attractive market products and may also imply and increase of nutritional value.
Amplified fragment length polymorphisms
Analysis of variance
Carotenoid cleavage dioxygenase
Composite interval mapping
- D :
Dark stem (gene)
- Di :
Discoidal fruit (gene)
Ethylene-responsive transcription factor
Flowering locus C protein
Flowering locus T protein
- gf :
Green flesh (gene)
logarithm of odds
- M :
Mottled or silvery leaves (gene)
Minimum allele frequency
OVATE family protein
Quantitative trait loci
Random amplified polymorphic DNA
Recombinant inbreed line
Singl nucleotide polymorphism
Simple sequence repeat
- W :
Weak rind coloration (gene)
- wf :
White flesh (gene)
This research was funded by the INIA project RTA2011-00044-C02-1/2 and E-RTA2013-00020-C04-03 of the Spanish Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA) cofunded with FEDER funds (EU).
This work has been carried out in the framework of the INIA projects RTA2011-00044-C02-1/2 and E-RTA2013-00020-C04-03 of the Spanish Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA) cofunded with FEDER funds (EU).
Availability of data and material
Most of the data generated or analyzed during this study are included in this published article and its supplementary information files. The remaining datasets generated are available in https://cucurbigene.upv.es/ and in the corresponding SRA archives of the NCBI indicated in the Results section.
BP, JC and JB designed the study. JMP, JB, and JC performed the bioinformatic analysis. BP, CE, EM and PG developed the RILs population. BP and EM phenotyped the RIL population. AJM contributed to the genetic analysis. BP, JMP, AJM, CE and JC drafted the manuscript. All authors read and approved the final version of the manuscript.
The authors declare that they have no competing interests.
Consent for publication
Ethics approval and consent to participate
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
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