Identification of QTL for Plant Architecture and Flowering Performance Traits in a Multi-Environment Evaluation of a Petunia axillaris × P. exserta Recombinant Inbred Line Population

Abstract

Field performance of herbaceous annual plants is largely determined by plant architecture and flowering performance. A Petunia axillaris × P. exserta F₇ recombinant inbred line population was grown in four field environments across the United States, and phenotyped for seven plant habit and flowering-related traits: plant height (Height), maximum (MaxWid) and minimum (MinWid) plant width, vigor, compactness (Comp), flowering canopy coverage (Flow) and flower color retention (ColorRet). Robust QTL (rQTL; QTL detected in two or more environments) were identified for all traits except minimum canopy width and were distributed across five of the seven Petunia chromosomes. The largest effect rQTL explained up to 23.8, 19.7, 16.7, 16, 25.7, and 36.9% of the observed phenotypic variation for Flow, Vigor, Comp, ColorRet, Height and MaxWid, respectively. rQTL for Flow, Comp, Height, and MaxWid colocalized on Chr 2, indicating this region could be particularly useful for mining candidate genes underlying important field performance traits in petunia.

1. Introduction

Petunia (Petunia ×hybrida) is a popular garden plant in the United States, ranking first among annual bedding plants with a wholesale sales value of $159.9 million in 2020 [1]. Plant architecture and flowering, including flower number, size, and persistence, are important aspects of petunia field performance. In addition to prolific flowering, desired traits for new cultivars include a compact growth habit, profuse lateral branching, and disease resistance. Petunia cultivars exist in a wide range of flower colors, flower sizes, and plant architectures, from upright to strongly prostrate growth. Despite this phenotypic variation, and despite most being F₁ hybrids, commercial petunia cultivars often exhibit low levels of heterozygosity [2], indicating a narrow germplasm pool for breeding.

Petunia is a horticultural hybrid derived from the progenitor species Petunia axillaris and Petunia integrifolia [3]. Most Petunia species are cross-compatible, though with varying degrees of fertility [4,5,6], and could thus serve as sources of novel alleles for introgression into petunia breeding lines. In fact, wild relative species have previously been used to bring novelty to petunia cultivars. For example, petunia cultivars traditionally exhibited an upright or mounded growth habit [7]. In the 1990s, the prostrate growth habit was introgressed from P. altiplana [2] with the release of petunia ‘Wave Purple’ and ‘Surfinia Red’, bringing about a major new cultivar market class. Subsequent utilization of prostrate-growing germplasm in petunia breeding programs led to the development of cultivars with a growth habit intermediate between prostrate and upright to varying degrees. However, introgressing desired alleles for a particular trait from wild germplasm will often bring other, undesirable alleles from linked loci [8] with the linkage being difficult to break. Development of dense linkage maps and identification of markers tightly linked with traits of interest can help to reduce this linkage drag [9].

We previously reported single nucleotide polymorphism (SNP) marker identification and genetic linkage map construction for a P. axillaris × P. exserta F₇ (AE) recombinant inbred line (RIL) population [10,11]. This population was subsequently evaluated under multiple controlled environment production conditions and quantitative trait loci (QTL) were identified for several important production-related traits, including plant height at flowering, flower bud number, time to flower, flower size, and lateral branch production [10,11]. However, these evaluations were focused on production-related traits, and data were collected at or prior to first flowering. QTL identification for petunia ornamental field performance has been limited to a single study with the AE RIL population [12] and a second study utilizing a RIL population derived from a P. integrifolia × P. axillaris interspecific hybrid [13], both occurring in Florida.

Field performance of petunia is largely determined by plant architecture, flowering performance (canopy coverage), and resistance to disease and insect pests. Desirable architectural traits include a compact growth habit (short internodes) and proliferous lateral branch production. Greenhouse evaluation of the petunia AE RIL population at three different temperatures revealed that plant height at flowering, lateral branch number, and internode length exhibited high broad-sense heritability [11]. A QTL for plant height that was significant at all three temperatures and explained up to 52% of the observed variation was identified on chromosome 4 [10]. Two QTL significant across the temperature range, explaining up to 23.6 and 36% of the observed variation, respectively, were identified on chromosome 3 [11].

Flowering performance is a function of several factors, including the number of flowers formed per inflorescence, the number of flowering branches and inflorescences developed, flower size, and flower longevity [11]. In greenhouse evaluations, we observed that P. axillaris developed more flower buds at first flowering than P. exserta, despite forming a similar number of flowering branches [11,14]. QTL flower bud number at first flowering significant across multiple temperatures and years were identified on chromosomes 1 and 4, with locus qFB4.2 having the largest effect, explaining up to 29% of the observed variation [11]. One QTL for the number of flowering branches (qFBN5.2) was significant across temperatures and years. However, this QTL only explained a maximum of 8.7% of the observed variation.

Persistence of flower color is another important attribute of flowering ornamental plants, as loss of pigmentation can reduce aesthetic value. Loss of pigmentation as flowers age has been documented in petunia [15], with mutations in the R2R3 MYB gene PH4 resulting in loss of anthocyanins and fading of flower color as flowers age in some genetic backgrounds [16]. The red flower color of P. exserta is unique within the genus and biochemically distinct from red-flowered cultivars of P. ×hybrida [17,18]. We have observed flower color fading among individuals in the AE RIL population (Warner, personal observation) but the genetic basis for this trait has not been evaluated.

The objectives of the current study were to: (1) understand trait relationships for the petunia AE RIL population in a diverse set of field environments and (2) identify QTL for important plant architecture and flowering traits for petunia field performance. Results from this work will facilitate marker-assisted breeding strategies and will aid in the identification of causal genes underlying control of these traits.

2. Materials and Methods

2.1. Plant Material and Growth Conditions

Two hundred F₇ P. axillaris (U.S. National Plant Germplasm System PI 667515) × P. exserta (PI OPGC 943) RILs (AE RILs) and the two parents were evaluated at four locations: Gilroy, CA (CA1), Buellton, CA (CA2), Huntersville, NC (NC), and Bellefonte, PA (PA). These locations represent four distinct climates throughout the United States, based on the Köppen-Geiger (KG) climate classification system [19]. KG climate types are Csb (temperate-dry summer-warm summer) for CA1, BSk (arid-steppe-cold) for CA2, Cfa (temperate-without dry season-warm summer) for NC, and Dfb (cold-without dry season-warm summer) for PA, while the native range of both P. axillaris and P. exserta [7] is primarily the Cfa climate type.

Seeds were sown in 128-cell trays (cell volume 12 mL) in April 2014 and germinated under intermittent mist. Seedlings were removed from mist and transplanted into 72-cell (cell volume 59 mL) trays when four true leaves were visible. Eight weeks after seed sow, RILs were transplanted into the field evaluation environment. Plantings at CA1, CA2, and PA were in ground beds, while the planting at NC was in 5.67 L round pots filled with soilless media and placed on a concrete pad.

At each location, three replicates were transplanted into the field except for NC, which had two replicates per RIL. All sites employed a randomized complete block design and plants within a replication were spaced on 36 cm centers. The plants were irrigated and fertilized according to standard practices at each trialing site. After 12 weeks in the field, plants were evaluated for estimated percentage canopy coverage with flowers, plant vigor (an estimate of total plant volume on a scale of 1–9, with 1 = low vigor and 9 = high vigor), plant compactness (scale 1–9, 1 = elongated internodes, 9 = very short internodes), plant height (measured from the soil line to the top of the plant canopy), and plant maximum width (measured as the widest span of the plant canopy) at all locations (

Table 1. List of traits measured and trait abbreviations.

Trait Description (Units)	Trait Abbreviation	QTL Abbreviation
Floral coverage of plant canopy (%)	Flow	FP
Plant vigor (1–9 scale)	Vigor	VIG
Plant compactness (1–9 scale)	Comp	COM
Plant height (cm)	Height	HGT
Plant maximum width (cm)	MaxWid	MAX
Plant minimum width (cm)	MinWid	MIN
Flower color retention (1–9 scale)	ColorRet	CR

). In addition, flower color retention (scale 1–9, 1 = severe fading, 9 = not faded) was assessed for RILs with non-white flowers at CA1, CA2, and NC, and plant minimum width (measured as the shortest span of the plant canopy) was measured at CA1 and CA2 only. To minimize variation, particularly for the traits scored on 1–9 scales, data were collected by the same individuals at each of the four evaluation sites.

2.2. Data Analysis

Data were analyzed using Statistical Analysis Software v9.4 (SAS Institute, Cary, NC, USA). Parental mean values for each trait at each location were compared by Student’s t-test. Pearson’s correlation coefficient were calculated between traits within each field site. Broad-sense heritability (H²) estimates were calculated for all evaluated traits as described by [20]. The equation was based on the variance component and calculated using the expected mean squares for each source $H^2=\frac{{\sigma }_g^2}{{\sigma }_g^2+{\sigma }_{\epsilon }^2}$ with ${\sigma }_g^2$ representing the genotypic variance and ${\sigma }_{\epsilon }^2$ the environmental variance. The variance of the environmental effect was calculated as ${\sigma }_{\epsilon }^2=\frac{{\sigma }_{gl}^2}{l}+\frac{{\sigma }_e^2}{rl}$ where ${\sigma }_{gl}^2$ is the variance among the locations, ${\sigma }_e^2$ is the residual, $l$ is the number of locations in the study, and $r$ is the number of replicates. At individual locations, broad-sense heritability was estimated using ${\sigma }_{\epsilon }^2=\frac{{\sigma }_e^2}{r}$ with terms as described above.

2.3. Marker Development, Linkage Map Construction, and QTL Mapping

The P. axillaris × P. exserta RIL population was genotyped and molecular markers generated as previously described [10]. Briefly, 6291 single nucleotide polymorphisms (SNPs) were employed to generate 368 bin markers based on recombination breakpoints [21]. From these, a genetic linkage map was generated that incorporated 356 of the bin markers [11] into linkage groups representing the seven petunia chromosomes. Chromosome (Chr) numbering was consistent with [22].

QTL mapping was conducted using the 163 RILs for which both phenotypic and genotypic data were available. The composite interval mapping Model 6 algorithm of the QTL Cartographer 2.5 software [23] was employed using the forward-backward regression method and parameters described by [11]. Logarithm of odds (LOD) values were determined for each QTL using likelihood-ratio statistics and the proportion of variation explained (%VE) by each QTL was estimated by R² values. MapChart 2.32 software [24] was used to visualize QTL using a subset of markers selected to be at least 1 cM apart to ease visualization. QTL names were assigned beginning with the designation “q” followed by the QTL trait abbreviation (Table 1), chromosome number, and the number order within a chromosome. QTL for the same trait at multiple locations having overlapping confidence intervals were denoted as robust QTL (rQTL).

3. Results

3.1. Trait Analysis

The P. axillaris × P. exserta RIL population exhibited a wide range of variation at all locations, with all traits displaying transgressive segregation in both directions at each location with the exception of Comp at NC, where P. axillaris was equal to the population minimum value (

Table 2. Descriptive statistics at four locations for field performance traits analyzed in a P. axillaris × P. exserta F₇ recombinant inbred line population.

	RILs					Parents
Trait z	n y	Mean	Sd	Min	Max	PA	PE	t-Test
Gilroy, CA (CA1)
Flow	538	52.9	25.81	0	90	53.3	66.7	xns
Vigor	539	4.9	1.44	1	9	6.3	4.3	*
Comp	539	4.1	1.08	1	7	3.3	2.3	ns
Height	539	42.9	9.86	13	69	41.3	42.0	ns
MaxWid	539	105.9	27.39	11	213	163.7	80.1	*
MinWid	446	87.6	25.68	10	163	121.3	71.3	*
ColorRet	331	4.0	1.87	1	8	wna	7.7
Buellton, CA (CA2)
Flow	591	54.4	22.55	0	90	50.0	73.3	ns
Vigor	595	4.3	1.22	1	8	5.7	4.0	*
Comp	595	4.1	1.11	1	8	3.3	5.3	*
Height	595	40.2	8.80	13	78	40.0	39.0	ns
MaxWid	595	98.7	24.65	13	173	160.5	76.0	*
MinWid	569	82.8	23.81	8	170	116.1	71.0	*
ColorRet	440	4.88	1.92	1	9	na	8.0
Huntersville, NC
Flow	397	41.11	21.22	0	80	45.0	55.0	ns
Vigor	397	5.92	2.21	1	9	8.0	7.0	ns
Comp	397	1.46	0.83	1	5	1.0	2.0	ns
Height	397	45.26	14.86	12	79	52.0	58.5	ns
MaxWid	397	111.71	35.16	7	196	157.0	115.0	*
Bellefonte, PA
Flow	584	45.99	20.74	0	80	30.0	40.0	ns
Vigor	584	5.52	2.18	1	9	6.0	4.7	ns
Comp	584	3.49	2.09	1	9	2.0	2.7	ns
Height	584	46.42	15.42	3	79	54.7	44.0	ns
MaxWid	584	116.11	34.02	8	176	130.3	98.3	*
ColorRet	429	5.72	1.86	1	9	na	7.0

^z Trait abbreviations as defined in Table 1. ^y n = sample number, Mean = population average, Sd = sample standard deviation, Min = minimum sample value, Max = maximum sample value, PA = Petunia axillaris, PE = Petunia exserta. ^xns and * indicate non-significance or significance at p < 0.05, respectively. ^wna = trait was not measured for this parent.

; Supplemental Figures S1–S4). Petunia axillaris had a greater MaxWid than P. exserta at all four locations, and a greater Vigor and MinWid at CA1 and CA2. (Table 2). Flow and Height were similar between the parental species at all locations, while Comp was similar at all sites except CA2. RILs grown at CA2 had the highest mean Flow at 54% while plants grown at NC had the lowest at 41% (Table 2).

Flow was positively correlated with Vigor, Height, and MaxWid at all four locations (

Table 3. Pearson’s correlation coefficients at different locations for field performance traits analyzed in P. axillaris × P. exserta F₇ recombinant inbred line population.

Trait z	Flow	Vigor	Comp	Height	MaxWid	MinWid
All locations
Vigor	0.49 ** y
Comp	0.12 **	−0.32 **
Height	0.34 **	0.65 **	−0.21 **
MaxWid	0.42 **	0.73 **	−0.32 **	0.62 **
MinWid	0.42 **	0.76 **	0.18 **	0.45 **	0.82 **
ColorRet	−0.19 **	0.07 *	−0.16 **	0.14 **	−0.03	−0.17 **
Gilroy, CA (CA1)
Vigor	0.61 **
Comp	0.50 **	0.42 **
Height	0.40 **	0.55 **	0.52 **
MaxWid	0.44 **	0.76 **	0.26 **	0.52 **
MinWid	0.47 **	0.77 **	0.29 **	0.49 **	0.83 **
ColorRet	−0.14 **	−0.11	−0.07	0.03	−0.15 *	−0.14 *
Buellton, CA (CA2)
Vigor	0.43 **
Comp	0.34 **	0.23 **
Height	0.11 *	0.45 **	0.26 **
MaxWid	0.36 **	0.76 **	0.08 *	0.43 **
MinWid	0.38 **	0.74 **	0.10 *	0.40 **	0.81 **
ColorRet	−0.15 *	−0.17 **	−0.01	0.12 *	−0.20 **	−0.15 *
Bellefonte, PA
Vigor	0.69 **
Comp	−0.37 **	−0.51 **
Height	0.55 **	0.76 **	−0.47 **
MaxWid	0.66 **	0.76 **	−0.68 **	0.70 **
ColorRet	−0.09	0.11 *	0.04	0.07	−0.11 *
Huntersville, NC
Vigor	0.74 **
Comp	−0.34 **	−0.47 **
Height	0.50 **	0.59 **	−0.44 **
MaxWid	0.48 **	0.64 **	−0.56 **	0.64 **

^z Trait abbreviations as defined in Table 1. ^y * and ** indicate significance at p < 0.05 and 0.001, respectively.

). Trait correlations were generally similar (in both direction and significance) across locations except for correlations between Comp and other traits. For example, Comp was correlated positively with Height and MaxWid at CA1 and CA2, but negatively at NC and PA.

Broad-sense heritability estimates for the evaluated traits were grouped into low (<0.30), moderate (0.30–0.60) or high (>0.60) as proposed by [25]. When considered across all locations, broad-sense heritability estimates were high for all traits except Comp. Within locations, heritabilities were high for all traits at PA and NC, and high for all traits except Comp (H² = 0.60) at CA2. At CA1, ColorRet H² was high (0.67), Flow was low (0.29), and all other traits exhibited moderate broad-sense heritability estimates (

Table 4. Broad-sense heritability (H²) estimates growth and flowering traits of a P. axillaris × P. exserta F₇ recombinant inbred line population at four locations.

Trait z	H2
	All locations	Buellton, CA	Gilroy, CA	Bellefonte, PA	Huntersville, NC
Flow	0.75	0.65	0.49	0.97	0.86
Vigor	0.77	0.77	0.55	0.96	0.88
Comp	0.74	0.60	0.45	0.93	0.90
Height	0.79	0.79	0.58	0.92	0.76
MaxWid	0.75	0.76	0.53	0.95	0.85
MinWid	0.68	0.72	0.40
ColorRet	0.79	0.71	0.67	0.99

^z Trait abbreviations as defined in Table 1.

).

3.2. QTL Analysis

A total of 79 QTL, with 15 of these being rQTL, were detected for seven traits at the four field locations (

Table 5. Summary of QTL identified at four field locations for the P. axillaris × P. exserta F₇ recombinant inbred line population. QTL identified at multiple locations with overlapping confidence intervals were considered robust QTL (rQTL) and are highlighted in bold.

Trait z	QTL	Chr	Nearest Marker	Loc.	Posit. (cm)	Interval (cm) y	LOD x	LOD Threshold w	A v	%VE u
Flow	qFP.1.1	1	AE_bin_78_1	CA1	8.81	6.8–9.1	2.76	2.66	−4.47	6.07
Flow	qFP.1.2	1	AE_bin_95_2	CA2	13.31	13.3–15.3	7.36	2.44	−6.65	14.20
Flow			AE_bin_95_2	NC	14.31	12.6–15.3	2.99	2.59	−4.85	5.88
Flow	qFP.2.1	2	AE_bin_58_12	NC	19.51	19.4–19.7	11.45	2.59	−10.27	23.81
Flow			AE_bin_61_3	PA	19.61	19.4–19.7	8.56	2.63	−10.97	18.95
Flow	qFP.2.2	2	AE_bin_52_48	CA2	20.21	19.9–21.2	2.94	2.44	−4.22	5.21
Flow	qFP.2.3	2	AE_bin_4_1	NC	27.71	25.7–28.8	5.17	2.59	−10.77	17.56
Flow	qFP.3.1	3	AE_bin_112_12	NC	31.41	27.9–33.8	2.84	2.59	5.07	4.92
Flow	qFP.4.1	4	AE_bin_187_4	PA	4.21	0–6.2	4.31	2.63	6.28	8.91
Flow			AE_bin_187_4	CA2	5.21	1.5–7.3	5.80	2.44	6.00	11.37
Flow	qFP.4.2	4	AE_bin_195_4	NC	11.91	10.6–14.3	3.07	2.59	4.76	5.65
Flow			AE_bin_197_3	CA2	14.31	12.8–14.5	4.81	2.44	5.35	9.02
Flow	qFP.4.3	4	AE_bin_207_2	CA1	25.01	24.1–25.4	3.04	2.66	5.10	6.77
Flow	qFP.6.1	6	AE_bin_236_1	CA2	10.11	8.1–13.2	3.04	2.44	−4.39	5.53
Vigor	qVIG.2.1	2	AE_bin_61_3	PA	19.61	19.4–19.7	12.56	2.74	−1.09	22.34
Vigor	qVIG.2.2	2	AE_bin_52_48	NC	20.01	19.9–20.5	17.41	2.65	−1.22	30.72
Vigor	qVIG.2.3	2	AE_bin_44_4	PA	21.61	21.1–21.8	12.82	2.74	−1.10	22.61
Vigor	qVIG.2.4	2	AE_bin_4_1	PA	28.71	26.4–30.5	5.17	2.74	−1.15	15.47
Vigor	qVIG.3.1	3	AE_bin_128_16_310_2	CA1	48.51	48.1–48.9	2.59	2.54	0.22	4.19
Vigor	qVIG.4.1	4	AE_bin_184_2	NC	0.01	0–1.0	8.68	2.65	0.79	13.85
Vigor	qVIG.4.2	4	AE_bin_187_4	CA2	4.21	2.6–6.6	11.28	2.65	0.55	26.01
Vigor	qVIG.4.3	4	AE_bin_197_3	CA2	14.31	12.2–14.4	11.79	2.65	0.56	27.08
Vigor	qVIG.4.4	4	AE_bin_198_1	CA1	17.21	15.2–18.3	6.27	2.54	0.44	14.05
Vigor	qVIG.4.5	4	AE_bin_229_48	CA1	26.61	26.4–26.9	10.86	2.54	0.51	19.71
Vigor				PA	26.61	26.4–27.1	3.05	2.74	0.51	4.62
Vigor	qVIG.4.6	4	AE_bin_201_1	CA2	27.81	27.4–29.9	5.19	2.65	0.37	9.37
Vigor	qVIG.6.1	6	AE_bin_239_2	NC	21.01	15.3–23.4	3.81	2.65	−0.65	5.41
Vigor	qVIG.6.2	6	AE_bin_252_5	NC	35.31	35.1–35.5	3.81	2.65	0.68	5.48
Vigor	qVIG.7.1	7	AE_bin_320_2	CA1	28.21	24.6–29.2	2.69	2.54	0.24	5.09
Comp	qCOMP.1.1	1	AE_bin_74_1	CA1	8.01	6.3–8.8	2.63	2.52	−0.18	5.28
Comp	qCOMP.1.2	1	AE_bin_91_6	CA2	11.51	10.9–11.6	8.25	2.48	−0.32	14.04
Comp	qCOMP.1.3	1	AE_bin_95_2	CA1	14.31	12.6–15.3	2.69	2.52	−0.19	5.91
Comp	qCOMP.2.1	2	AE_bin_6_1	CA2	0.01	0–3.4	2.59	2.48	−0.20	4.23
Comp	qCOMP.2.2	2	AE_bin_16_7	CA2	10.21	9.5–10.8	6.50	2.48	−0.32	12.92
Comp	qCOMP.2.3	2	AE_bin_31_10	NC	18.21	18.0–19.0	6.65	2.49	0.34	15.28
Comp	qCOMP.2.4	2	AE_bin_55_14	CA2	19.41	19.3–19.4	8.19	2.48	0.36	13.71
Comp			AE_bin_58_12	PA	19.51	19.3–19.6	7.42	2.68	0.81	14.84
Comp	qCOMP.2.5	2	AE_bin_28_3	NC	24.31	23.9–26.7	7.31	2.49	0.36	16.67
Comp			AE_bin_4_1	PA	28.71	26.3–29.3	3.20	2.68	1.05	14.70
Comp	qCOMP.2.6	2	AE_bin_3_202_229_1	CA1	32.61	31.7–33.6	3.61	2.52	−0.30	7.17
Comp	qCOMP.4.1	4	AE_bin_206_4	PA	24.11	23.3–24.9	5.59	2.68	−0.67	10.81
Comp	qCOMP.5.1	5	AE_bin_290_8	PA	10.31	8.4–11.6	2.72	2.68	−0.45	5.06
Comp	qCOMP.5.2	5	AE_bin_295_2	CA1	15.01	13.9–17.6	4.50	2.52	0.24	9.62
Comp	qCOMP.7.1	7	AE_bin_315_1	CA2	22.41	20.5–24.1	3.18	2.48	−0.19	4.88
ColorRet	qCR.2.1	2	AE_bin_15_11	PA	9.81	8.9–10.5	4.00	2.68	−0.65	9.55
ColorRet	qCR.2.2	2	AE_bin_50_8	PA	19.21	19.1–19.3	7.10	2.68	−0.95	15.95
ColorRet	qCR.2.3	2	AE_bin_4_1	PA	27.71	25.2–28.7	3.74	2.68	−1.10	14.13
ColorRet	qCR.3.1	3	AE_bin_165_1	PA	69.71	68.0–70.3	3.26	2.68	−0.53	7.87
ColorRet	qCR.3.2	3	AE_bin_163_1	CA2	71.61	71.2–72.1	4.11	2.59	−0.58	9.50
ColorRet	qCR.3.3	3	AE_bin_180_16	CA2	73.41	73.1–73.6	4.71	2.59	−0.61	10.72
ColorRet			AE_bin_177_199_237_1	CA1	73.51	73.3–73.7	6.20	2.66	−0.72	14.87
ColorRet	qCR.6.1	6	AE_bin_244_6	PA	25.61	23.4–26.6	4.59	2.68	−0.66	9.90
ColorRet	qCR.6.2	6	AE_bin_263_50_86_2	PA	32.01	30.6–32.3	3.94	2.68	−0.59	8.30
ColorRet	qCR.7.1	7	AE_bin_318_1	PA	20.21	20.1–22.1	4.34	2.68	−0.57	9.58
ColorRet			AE_bin_316_1	CA2	21.11	20.8–22.4	5.92	2.59	−0.68	15.97
ColorRet	qCR.7.2	7	AE_bin_324_45	PA	30.21	29.4–30.8	4.87	2.68	−0.60	10.33
ColorRet	qCR.7.3	7	AE_bin_329_7	CA2	32.01	31.1–33.0	5.97	2.59	−0.65	14.46
MaxWid	qMAX.1.1	1	AE_bin_64_2	CA1	0.01	0–1.2	3.83	2.58	5.46	6.82
MaxWid	qMAX.1.2	1	AE_bin_82_5	CA1	11.31	11.0–11.5	4.90	2.58	6.13	8.49
MaxWid	qMAX.2.1	2	AE_bin_55_14	NC	19.41	19.3–19.4	17.23	2.54	−20.75	36.88
MaxWid			AE_bin_58_12	PA	19.51	19.3–19.7	11.62	2.71	−15.60	19.27
MaxWid	qMAX.2.2	2	AE_bin_27_2	NC	24.11	23.4–24.3	13.88	2.54	−20.03	31.34
MaxWid	qMAX.4.1	4	AE_bin_185_1	CA2	1.71	0.3–7.2	5.03	2.68	6.97	8.51
MaxWid				PA	1.71	0.8–3.7	6.46	2.71	11.47	9.73
MaxWid	qMAX.4.2	4	AE_bin_193_1	CA2	11.11	10.9–11.2	10.16	2.68	10.17	22.27
MaxWid	qMAX.4.3	4	AE_bin_231_1	CA1	16.21	15.1–17.4	8.96	2.58	9.34	19.43
MaxWid			AE_bin_198_1	CA2	17.21	15.9–21	5.97	2.68	8.22	12.08
MaxWid			AE_bin_199_3	PA	18.71	17.9–21.2	4.46	2.71	9.29	6.52
MaxWid	qMAX.4.4	4	AE_bin_207_2	CA1	25.01	24.6–25.6	10.47	2.58	9.45	19.44
MaxWid	qMAX.4.5	4	AE_bin_210_117_218_4_2_1	CA2	26.01	25.9–26.1	5.51	2.68	7.28	9.68
MaxWid	qMAX.4.6	4	AE_bin_229_48	CA1	26.61	26.4–26.9	10.94	2.58	9.56	20.08
MaxWid			AE_bin_226_1	PA	27.01	26.4–27.5	4.54	2.71	9.15	6.65
MinWid	qMIN.4.1	4	AE_bin_187_4	CA2	5.21	4.9–7.3	5.84	2.65	7.40	11.26
MinWid	qMIN.4.2	4	AE_bin_231_1	CA1	16.21	16.0–17.5	8.02	2.63	9.43	20.64
MinWid	qMIN.4.3	4	AE_bin_200_2	CA2	19.11	18.7–20.8	7.44	2.65	8.09	13.61
MinWid	qMIN.4.4	4	AE_bin_207_2	CA1	25.01	24.9–25.3	10.67	2.63	9.99	23.37
MinWid	qMIN.4.5	4	AE_bin_229_48	CA1	26.61	26.4–27.4	10.66	2.63	10.00	23.31
MinWid	qMIN.7.1	7	AE_bin_218_4	CA1	33.01	31.0–34.0	3.26	2.63	5.48	6.84
Height	qHGT.2.1	2	AE_bin_7_5	PA	2.91	0–4.9	2.73	2.61	−4.20	6.85
Height	qHGT.2.2	2	AE_bin_17_3	PA	11.01	10.8–11.4	5.73	2.61	−5.45	11.27
Height	qHGT.2.3	2	AE_bin_30_1	NC	17.91	16.8–18.2	6.96	2.84	−5.98	14.89
Height	qHGT.2.4	2	AE_bin_50_8	PA	19.21	18.7–19.4	14.01	2.61	−7.92	24.56
Height			AE_bin_61_3	NC	19.61	19.3–19.9	7.89	2.84	−6.02	16.23
Height	qHGT.2.5	2	AE_bin_49_8	CA1	20.61	20.2–20.7	4.04	2.60	−2.21	7.48
Height	qHGT.2.6	2	AE_bin_44_4	PA	21.61	21.1–21.8	14.88	2.61	−8.13	25.71
Height			AE_bin_43_2	CA2	21.81	21.6–21.9	9.96	2.67	−3.20	15.92
Height	qHGT.2.7	2	AE_bin_27_2	NC	24.11	22.8–24.3	6.74	2.84	−5.95	14.33
Height	qHGT.2.8	2	AE_bin_4_1	PA	28.71	26.9–31.3	8.80	2.61	−9.78	23.59
Height	qHGT.2.9	2	AE_bin_3_202_229_2	CA2	32.41	32.2–32.6	6.88	2.67	−3.54	11.38
Height	qHGT.4.1	4	AE_bin_187_4	PA	4.21	4.0–6.7	3.89	2.61	4.83	9.19
Height	qHGT.4.2	4	AE_bin_206_4	CA2	24.11	23.3–24.8	6.27	2.67	2.52	8.72
Height	qHGT.4.3	4	AE_bin_229_48	CA1	26.61	26.4–27.1	5.59	2.60	2.49	9.39
Height	qHGT.5.1	5	AE_bin_288_1	CA1	7.01	5.0–8.4	4.29	2.60	2.24	8.26
Height	qHGT.5.2	5	AE_bin_299_1	CA2	13.31	12.9–13.4	7.21	2.67	2.51	10.41
Height	qHGT.7.1	7	AE_bin_314_2	CA2	22.91	22.1–24.5	2.84	2.67	−1.47	3.53

^z Trait abbreviations: as defined in Table 1. ^y Confidence interval as determined by 1-LOD values. ^x LOD values calculated from the likelihood-ratio statistics. ^w LOD threshold determined at 0.05 probability based on 1000 permutations. ^v Additive effect of QTL, positive values indicate beneficial alleles from P. axillaris. ^u Percentage of variation explained by QTL estimated using R² statistics.

). The most QTL detected were for Height with 16 QTL while only six QTL were detected for MinWid. However, MinWid was only determined at only two of the four locations. The two Flow QTL explaining the greatest phenotypic variation, qFP.2.3 (17.6%) and the rQTL qFP.2.1 (up to 23.8%), also had the greatest additive effect of 10.8 and 10.3%, respectively (Table 5). A total of four rQTL for Flow were detected on Chr 1, 2 and 4 (Table 5; Figure 1). Petunia exserta contributed the beneficial allele for each of the Flow rQTL on Chr 1 and 2, whereas P. axillaris contributed the beneficial allele for the two rQTL on Chr 4.

Only one rQTL was detected for Vigor. This QTL explained up to 19.7% of the phenotypic variation and was located on Chr 4 (Table 5; Figure 1), with P. axillaris providing positive additivity of 0.51 units (on a subjective 1–9 scale). Another QTL for Vigor, qVIG.2.2, explained 30.7% of the variation and had the greatest additive effect of 1.22. Petunia exserta contributed the beneficial allele for this major QTL, and P. axillaris contributed.

The beneficial allele for two other major QTL for Height. However, each of the three major QTL were only detected at one location, though qVIG.2.1 and qVIG.2.2 nearly overlapped.

There were two rQTL detected for Height that explained up to 24.6% (qHGT.2.4) and 25.7% (qHGT.2.6) of the observed variation (Table 5; Figure 1). Both rQTL were located on Chr 2 and had beneficial alleles contributed by P. exserta. For MaxWid, four rQTL were detected. Three of these rQTL were located on Chr 4 and had beneficial alleles from P. axillaris. One MaxWid rQTL (qMAX.2.1), detected on Chr 2 explained the greatest amount phenotypic variation (36.9%), and had the greatest additive effect of 20.8 cm. P. exserta contributed the beneficial allele for this rQTL and for the major QTL qMAX.2.2, which explained 31.3% of the variation and had the second greatest additive effect of 20.0 cm.

The 15 rQTL for the six traits in four locations were detected on all chromosomes except for Chr 5 and 6 (Table 5; Figure 1). Chr 2 and 4 both had six rQTL, whereas Chr 1, 3, and 7 each had 1 rQTL. On Chr 2, four of the six rQTL for each trait—Flow, Compact, MaxWid, and Height—co-localized to a 0.4 cm region. Comparatively, the six rQTL on Chr 4 were spread across three regions with two co-localizing rQTL for two traits at each region. Including QTL significant at only a single location, overall, P. exserta contributed more beneficial alleles for QTL for Flow (six vs. four for P. axillaris), Comp (nine vs. five), Height (eleven vs. five), and all the QTL for ColorRet, whereas P. axillaris contributed more beneficial alleles for the QTL for Vigor (nine vs. five) and MaxWid eight vs. 2), and all the QTL for MinWid.

4. Discussion

Plant habit and flowering performance, including floral production and persistence of floral pigmentation, are critical traits for field performance of ornamental plants. Here we have described the first multi-environment QTL analysis for field performance traits in petunia by employing an interspecific Petunia RIL population grown in a diverse set of field environments. Crop wild relatives can provide desirable alleles for improvement of domesticated crops. Given the high crossability between P. axillaris (a progenitor of P. ×hybrida), P. exserta, and the cultivated P. ×hybrida [5,6], these species may be desirable sources of novelty or trait improvement for cultivated petunia.

The P. axillaris × P. exserta RIL population exhibited transgressive segregation for all traits at most locations (Table 2; Supplemental Figures S1–S4). Additionally, population distributions were generally normal, suggesting that multiple genes are involved in the control of these traits. This RIL population was previously evaluated in a two-year field trial in Wimauma, Florida [12]. Three similar traits were evaluated between the two studies: MaxWid, Height, and Flow. Height, MaxWid, and Flow all expressed transgressive segregation in Florida field trial [12], and Height also expressed similar transgressive segregation previously in a greenhouse trial at three temperatures [11].

Broad-sense heritability estimates for all traits, except for Comp, were generally high across environments, suggesting that the evaluated traits can be selected for during breeding. Petunia height H² has been previously reported to be high in multiple populations and both field and greenhouse environments [11,12,13,26]. The lower H² for Comp across locations is perhaps not surprising, as internode length is highly sensitive to variation in environmental variables, including day-night temperature differences [27], irradiance level [28], and wind speed [29]. Despite the lower H², two rQTL for Comp were identified on Chr 2 (Table 5).

Balancing robust vegetative growth with prolific flowering is critical for performance of most herbaceous annual ornamental crops. Most growth-related traits were positively correlated with each other at all locations (Table 3). Additionally, Flow was positively correlated with the growth-related traits Height, MaxWid, and overall Vigor at each location, and with MinWid at the two locations at which this trait was measured, indicating that robust vegetative growth did not reduce flowering performance.

Of the traits evaluated both in the current study and the previous field evaluation (Flow, Height, and MaxWid) [12], some common QTL, including rQTL, were identified and provide interesting targets for candidate gene mining. The MaxWid rQTL qMAX.4.1 colocalized and had the same nearest marker as the only QTL for plant spread (calculated as maximum plant width divided by plant width perpendicular to the maximum width) identified in both years of the previous study [12]. In both studies, P. axillaris provided positive additivity at this locus. One of the two QTL for Height identified by Cao et al. [12] colocalized with a Height QTL identified in the current study, having the same nearest marker (AE_bin_4_1) as qHGT.2.8. However, this QTL was only significant at one location (PA) in the current study.

Of the four total rQTL identified for Flow, two Flow rQTL (qFP.1.2 and qFP.4.1) from the current study colocalized with QTL for flower count that were significant in both years of the Cao et al. [12] study, with the same parent as previously reported providing positive additivity at these loci (P. exserta for qFP.1.2 and P. axillaris for qFP.4.2; Table 5). These results both highlight the potential importance of these regions in regulating flower production in petunia and indicate that our method of estimating floral canopy coverage was similarly effective in identifying QTL for flowering intensity as the more labor-intensive manual counting of all flowers in the plant canopy. A third flower count QTL reported by Cao et al. mapped close to the rQTL qFP.2.1 and single environment QTL qFP.2.2 but did not overlap either narrow region. We also previously evaluated this population for flowering related traits at first flowering in a greenhouse trial at three temperatures [11]. One of the traits evaluated was total flower bud number upon initial flowering (i.e., when the first flower opened). Only one rQTL from that study colocalized with any Flow QTL from the current study, and that QTL (qFP.4.3) was only significant at CA1. This suggests that the genetic factors that regulate initial flower bud production by young plants and floral coverage of mature plant canopies may be largely distinct.

We identified two rQTL for ColorRet, on Chr 3 and Chr 7. Mutant alleles of two petunia genes, ph4 and specific an1 alleles, formerly known as ph6 alleles [30], have previously been associated with flower color fading in some genetic backgrounds [16]. PH4 and AN1 have been mapped to Chr 3 and Chr 6, respectively, in classical genetic studies [31]. PH4 is located on P. axillaris genome scaffold Peaxi162Scf00349 [3]. Unfortunately, the SNPs employed in the current study did not allow us to place PH4 on the linkage map. Therefore, it is unclear if PH4 underlies the ColorRet rQTL on Chr 3. AN1 is located on scaffold Peaxi162Scf00338. A bin marker (AE_bin_262_163) containing a SNP physically located ca. 0.16 Mb from AN1 on that scaffold [10] colocalized with the ColorRet QTL qCR.6.2. However, this QTL was only significant at PA. The rQTL for ColorRet identified on Chr 7 appears to represent a novel locus associated with flower color retention in petunia.

5. Conclusions

The present work identifies genomic regions and molecular markers that may be useful for breeding new petunia cultivars with desirable field performance traits including extensive floral canopy coverage, compact growth habit, and persistent floral color retention. Additionally, this work will aid in the identification of candidate genes underlying important field performance traits. Of particular interest for further evaluation is a region on chromosome 2 harboring co-localizing QTL for floral canopy coverage, plant height, plant maximum width, and compactness. Additionally, this work identifies AE RILs that may be useful breeding lines to improve field performance as they combine prolific flowering, compact growth habit, and high vigor.