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. 2020 Apr 17;26(5):1021–1034. doi: 10.1007/s12298-020-00800-7

Mapping QTLs for 15 morpho-metric traits in Arabidopsis thaliana using Col-0 × Don-0 population

Astha Gupta 1,2,3, Vandana Jaiswal 1, Samir V Sawant 1,2,✉, Hemant Kumar Yadav 1,2,✉
PMCID: PMC7196571  PMID: 32377050

Abstract

Genome wide quantitative trait loci (QTL) mapping was conducted in Arabidopsis thaliana using F2 mapping population (Col-0 × Don-0) and SNPs markers. A total of five linkage groups were obtained with number of SNPs varying from 45 to 59 per linkage group. The composite interval mapping detected a total of 36 QTLs for 15 traits and the number of QTLs ranged from one (root length, root dry biomass, cauline leaf width, number of internodes and internode distance) to seven (for bolting days). The range of phenotypic variance explained (PVE) and logarithm of the odds ratio of these 36 QTLs was found be 0.19–38.17% and 3.0–6.26 respectively. Further, the epistatic interaction detected one main effect QTL and four epistatic QTLs. Five major QTLs viz. Qbd.nbri.4.3, Qfd.nbri.4.2, Qrdm.nbri.5.1, Qncl.nbri.2.2, Qtd.nbri.4.1 with PVE > 15.0% might be useful for fine mapping to identify genes associated with respective traits, and also for development of specialized population through marker assisted selection. The identification of additive and dominant effect QTLs and desirable alleles of each of above mentioned traits would also be important for future research.

Electronic supplementary material

The online version of this article (10.1007/s12298-020-00800-7) contains supplementary material, which is available to authorized users.

Keywords: Arabidopsis, Phenotyping, Mapping population, Single nucleotide polymorphism (SNP), QTL mapping

Introduction

Arabidopsis thaliana is considered as model plant and utilized for vast studies including molecular biology, genetics, molecular breeding due to its short life cycle, small genome size (135 Mb with five chromosomes; ~ 27,000 genes; Bevan and Murphy 1999) and easily transformation features (Meinke et al. 1998). For genetic dissection of complex traits, linkage mapping is an important and widely used approach. The various types of molecular markers such as SSR (Bloomer et al. 2014), AFLP (Keurentjes et al. 2007), SSLP (Kellermeier et al. 2013) and SNPs (Alhajturki et al. 2018) have been substantially utilized for mapping QTLs in Arabidopsis. A number of QTLs have been identified in Arabidopsis for specific traits using mapping population derived from different sets of ecotypes (Simon et al. 2008; Alhajturki et al. 2018). However, the ecotype Don-0 has not been yet utilized extensively in previous studies especially with Col-0. To identify novel QTLs/genes for important traits, new mapping population using new ecotypes needs to be explored. However, diversity between the ecotypes is initial step to select parents for mapping population development and QTL mapping. Moreover, Col-0 and Don-0 showed ecological, molecular (Wang et al. 2012) and morphological variations for various traits in addition to high number of unique SNPs (Cao et al. 2011). Therefore, in the present investigation, Don-0 was selected along with Col-0 (widely used ecotype of A. thaliana) for constructing mapping population to detect the QTLs for 15 traits. Previously, the Don-0 × Ler derived mapping population has been used to detect QTLs that identified some new and more active alleles for flowering time and leaf number (Méndez-Vigo et al. 2016). Till date, no systematic efforts have been made to investigate the shoot and root trait related QTLs using Col-0 × Don-0 which could be further utilized to explore the trait-related elite genes, metabolic pathways and biological processes. Therefore, present investigation has been undertaken to explore the biomass (shoot and root traits) related QTLs in A. thaliana using Col-0 × Don-0 derived mapping population.

Materials and methods

Parental lines and mapping population

The two ecotypes of A. thaliana viz. Col-0 and Don-0 was selected as parental lines to develop F2 mapping population The seeds of these two ecotypes were procured from Arabidopsis Biological Resource Center (ABRC), Ohio State University (https://abrc.osu.edu/). The Col-0 was used as female and Don-0 as male parent for crossing to develop F1 hybrid. The F1 hybrid was confirmed using polymorphic SNPs among the parental lines. The true selected F1 hybrid was selfed and seeds for F2 population were harvested. More than 250 F2 plants were raised in culture facility at CSIR-NBRI, Lucknow. Finally, a total of 186 F2 plants were used for phenotyping and genotyping to develop linkage map and tag QTLs for various traits.

Phenotyping of mapping population for quantitative traits

The F2 population along with parents (Col-0 and Don-0) was raised in Arabidopsis culture facility at 22 °C temperature, 80% humidity and long day condition (16 h light and 8 h dark). Each F2 plants was sown in single pot and phenotypic data for 15 traits were recorded. The phenotypic traits included (1) bolting days, (2) days to flowering, (3) rosette diameter, (4) rosette leaf length, (5) rosette leaf width, (6) number of rosette leaves, (7) root length, (8) root dry biomass, (9) number of cauline leaves, (10) cauline leaf length, (11) cauline leaf width, (12) trichome density, (13) number of internodes, (14) internode distance and (15) plant height. The basic descriptive statistics including range, mean and standard deviation of each trait was calculated in Microsoft Office Excel. The frequency distribution curve and Pearson’s correlation coefficient was analyzed using SPSS 17.0.

DNA isolation, SNP assay and genotyping

The total genomic DNA was isolated from fresh and young leaves using DNAzol (Invitrogen following manufacture’s protocol). The quality of genomic DNA was checked on 0.8% agarose and quantity estimated using Fluorometer (Qubit, Invitrogen). Further, the genomic DNA was normalized to 10 ηg/µl for PCR amplification. The SNP sequence data (working variants with reference) of Col-0 and Don-0 ecotypes was downloaded from 1001 Genomes-A Catalog of A. thaliana Genetic Variation (http://1001genomes.org/). A set of 100 SNPs from each chromosome were selected considering more or less equal distance among the SNPs. In this way, a set of 500 sequences of 401 bp length each (200 bases up and downstream of the selected SNP) were extracted for designing SNP assay. The SNP containing sequences were subjected to design SNP specific primers using MassARRAY Assay Design 3.0 software (Sequenom Inc, San Diego, California). The SNP genotyping was carried out on Sequenom™ MassARRAY platform using iPLEX™ protocol as described by the manufacturer (Oeth et al. 2005). The SNP data obtained were tested for Mendelian segregation ratio using Chi square test of goodness of fit.

Construction of framework linkage map

The SNP data with adequate Mendelian segregation was used for linkage map construction through ‘MAPMAKER/EXP, version 3.0 software (Lander et al. 1987). The threshold logarithm of the odds ratio (LOD) was set to 3.0 and recombination fraction was converted to centimorgan with Kosambi mapping function (Kosambi 1943). The constructed linkage groups were assigned to chromosomes by the comparison of genetic and physical position of SNPs. The graphical representation of the linkage groups was drawn using software MapChart version 2.2 (Voorrips 2002).

Identification of QTLs

The composite interval mapping (CIM) analysis was conducted for identification of QTLs using QTL Cartographer version 2.5 (Basten et al. 2005). The threshold LOD for each trait was calculated using 1000 permutations at p ≥ 0.05. A minimum LOD score of 3.0 was used to identify probable QTLs, however, QTLs with above threshold LOD were considered as definitive QTLs. The confidence interval (CI) was calculated by marking positions ± 1 LOD from the peak. The relative contribution of genetic component (R2) was calculated as the proportion of the phenotypic variation explained (PVE). The QTLs explaining more than 15% PVE were considered as major QTLs. The QTL action (dominant/additive) was determined following Stuber et al. (1987).

The epistatic interaction was analysed through mixed-model-based composite interval mapping (MCIM; Wang et al. 1999) using software QTL Network v2.0 (Yang et al. 2007) to identify main effect QTLs (M-QTLs) and epistatic QTLs (E-QTLs). For identification of epistatic QTLs, analysis was conducted with 1 cM walking speed and 2D genome scan. The identified QTLs were named following standard nomenclature system (McIntosh et al. 2001). The regions that presented QTLs were analyzed using Map Viewer feature of NCBI (https://www.ncbi.nlm.nih.gov/) for gene identifications.

Results

Phenotypic variation and correlation analysis

The ecotype Col-0 and Don-0 showed considerable level of variability for most of the traits evaluated during the present study (Fig. 1; Table 1). The Col-0 was early bolted and flowered earlier (56.00 and 61.33 days respectively) compared to Don-0 (101.3 and 109.5 days). The rosette of Don-0 (8.77 cm) was larger than Col-0 (6.60 cm; Fig. 1a). The rosette leaf width of Col-0 (1.59 cm) was found to be broader that Don-0 (1.45 cm) (Fig. 1g). The number of rosette leaves (50.67 leaves) and cauline leaves (92.67) of Don-0 was recorded higher than of Col-0 (33.83 and 50.50 leaves respectively). The root length (19.67 cm) and root dry biomass (0.55 g) of Don-0 was also noticed higher than of Col-0 (14.77 cm, 0.20 g) (Fig. 1e). The cauline leaf length (2.79 cm) and width (1.34 cm) of Col-0 were larger than that in Don-0 (2.02 cm and 0.54 cm) (Fig. 1f). The trichome density on mature leaf was found to be high in Col-0 (25.61 in 0.5 cm2) as compared to Don-0 (17.19 in 0.5 cm2). Number of internodes (3.67) and internode distance (2.01 cm) of Col-0 were less than Don-0 (internode number and distance: 3.83 and 2.47 cm). Maximum plant height was measured in Don-0 (37.57 cm) as compared to Col-0 (33.90 cm).

Fig. 1.

Fig. 1

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Pictorial representation of differences between Col-0 and Don-0 for rosette diameter and biomass (a); number of cauline leaves and internodes (b); plant height (c); trichome density (d); flowering and root biomass (e); cauline leaf (f); rosette leaf (g)

Table 1.

Phenotypic variation for 15 traits in parental genotypes (Col-0 and Don-0) and derived F2 population

Traits Col-0 Don-0 Phenotypic variation in 186 F2 plants
Min Max Mean ± SD
Bolting days 56.00 101.33 35.00 208.00 131.90 ± 30.07
Days to flowering 61.33 109.50 47.00 228.00 150.86 ± 32.83
Rosette diameter (cm) 6.60 8.77 1.50 20.00 10.66 ± 2.65
Rosette leaf length (cm) 3.12 4.51 1.27 6.97 3.51 ± 0.98
Rosette leaf width (cm) 1.59 1.45 0.87 2.93 1.84 ± 0.44
No. of rosette leaves 33.83 50.67 20.00 186.00 80.44 ± 30.30
Root length (cm) 14.77 19.67 6.10 34.00 18.80 ± 4.21
Root dry biomass (g) 0.20 0.55 0.01 0.62 0.20 ± 0.11
No. of cauline leaves 50.50 92.67 12.00 120.00 45.81 ± 21.52
Cauline leaf length (cm) 2.79 2.02 0.77 4.00 2.22 ± 0.64
Cauline leaf width (cm) 1.34 0.54 0.43 1.97 1.08 ± 0.37
Trichome density (0.5 cm2) 25.61 17.19 5.11 63.71 22.52 ± 10.39
No of internodes 3.67 3.83 3.00 14.00 7.35 ± 2.15
Internode distance (cm) 2.01 2.47 0.77 4.50 2.48 ± 0.72
Plant height (cm) 33.90 37.57 3.00 67.00 36.49 ± 10.97
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The hybrid derived from Col-0 × Don-0 was tested through 46 SNPs (Supplementary Fig. S1) and advanced to F2 population. The phenotypic variations of each trait in F2 population of 186 F2 plants are presented in Table 1. The F2 population showed wide range of phenotypic variations for most of the traits (Fig. 2) and had normal distribution of data, although transgressive segregation was also observed (Fig. 3). Phenotypic data of F2 population was subjected to correlation coefficient analysis to understand the relationship among the traits. Out of 105 pairs of traits, only six trait-pairs were found to be significantly and positively correlated and significant at 5% and 1% level (Table 2). Out of six significant correlations, five correlations associated to rosette related traits including rosette diameter, rosette leaf length, rosette leaf width and number; all the four rosette related trait were correlated except rosette leaf width/number. Significant positive correlation (0.92** significant at 1% level) was observed between bolting days and days to flowering. Moreover, negative correlation (equal/above to − 0.20) was found between cauline leaf (length and cauline leaf width) with days to flowering and bolting days; trichome density with rosette leaf (length and width) and internode distance, plant height with days to flowering and bolting days. It was investigated that resulted negative correlation was non-significant for most of the evaluated traits, therefore this information will not be very useful for further analysis.

Fig. 2.

Fig. 2

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Representative phenotypic variations in F2 plants for rosette leaf size, shape and number, bolting, flowering (a); trichome density (b); cauline leaves and plant height (c); root length and biomass (d); internode distance and number (e)

Fig. 3.

Fig. 3

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Frequency distribution of 15 traits in F2 population. Red and blue stars represent trait value of Col-0 and Don-0 respectively (color figure online)

Table 2.

Pearsons correlation coefficients among 15 phenotypic traits in F2 mapping population derived from the cross Col-0 × Don-0

Traits Days to flowering Rosette diameter Rosette leaf length Rosette leaf width No. of rosette leaves Root length Root dry biomass No. of cauline leaves Caulin leaf length Cauline leaf width Trichome density No. of internods Internode distance Plant height
Bolting days 0.92** − 0.06 − 0.07 − 0.05 − 0.10 − 0.14 − 0.19 − 0.15 − 0.28 − 0.24 − 0.12 0.09 − 0.08 − 0.24
Days to flowering − 0.06 − 0.09 − 0.06 − 0.07 − 0.15 − 0.13 − 0.11 − 0.31 − 0.27 − 0.10 0.12 − 0.12 − 0.27
Rosette diameter 0.84** 0.68** 0.63** 0.11 0.23 0.32 0.37 0.31 − 0.15 0.05 0.02 0.26
Rosette leaf length 0.73** 0.53* 0.11 0.15 0.33 0.31 0.26 − 0.24 0.06 0.08 0.26
Rosette leaf width 0.37 0.00 0.11 0.21 0.27 0.32 − 0.20 0.04 0.11 0.28
No. of rosette leaves 0.12 0.32 0.33 0.24 0.14 − 0.01 0.02 − 0.07 0.12
Root length 0.34 0.15 0.21 0.18 0.00 0.00 0.07 0.19
Root dry biomass 0.31 0.31 0.24 0.10 − 0.05 − 0.14 0.18
No of cauline leaves 0.35 0.25 − 0.06 0.19 0.14 0.32
Cauline leaf length 0.77 − 0.13 − 0.02 0.24 0.44
Cauline leaf width − 0.09 − 0.18 0.21 0.31
Trichome density − 0.13 − 0.20 − 0.07
No. of internodes 0.01 0.21
Internode distance 0.31
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*, **Significant at 5% and 1% respectively

Polymorphic markers and segregation analysis

Out of 410, a total of 364 SNPs were found to be polymorphic among the parents (Col-0 and Don-0) and of which 341 were successfully obtained genotyping 186 F2 plants. The Chi square test of goodness of fit revealed that out of 341 SNPs, 11 SNPs showed significant distortion from Mendelian segregation (Supplementary Table S1), and thus excluded from further analysis. Finally, a set of 330 SNPs were selected and utilized for linkage map construction and identification of QTLs.

Construction of linkage map and QTL identification through composite interval mapping analysis

With the data of 330 SNPs, 5 linkage groups (LG1–LG5) were constructed (Fig. 4) comprising 262 SNPs. The other 68 SNPs were found to be unlinked. The linkage groups (LG1–LG5) correspond to Arabidopsis chromosomes (Chr1–Chr5) as shown in Fig. 4. The composite interval mapping detected a total of 36 QTLs for 15 traits distributed on all five linkage groups (Table 3). Out of 36 QTLs, 7 QTLs were found to be definitive (above threshold LOD) and 29 were as probable QTLs (LOD score more than 3.0 but below threshold). The 7 definitive QTLs were found to be associated with 5 traits including bolting days (2 QTLs), days to flowering (2 QTLs), rosette leaf length (1 QTL), cauline leaf length (1 QTL and plant height (1 QTL). The maximum number of QTLs (7) was identified for bolting days, followed by 4 QTLs for rosette leaf width and cauline leaf length; 3 QTLs for days to flowering and number of cauline leaves; 2 QTLs for rosette diameter, rosette leaf length, number of rosette leaves, trichome density and plant height; and minimum 1 QTL for root length, root dry biomass, cauline leaf width, number of internodes and internode distance. The PVE of individual QTL ranged from 0.19% (number of rosette leaves) to 38.17% (number of cauline leaves) with an average of 9.67%. Out of 36 QTLs, 5 were found to be major QTLs explaining more than 15% of total phenotypic variation. These five major QTLs includes- one each for bolting days (Qbd.nbri.4.3; PVE = 28.1%), days to flowering (Qfd.nbri.4.2; PVE = 25.5%), roots dry biomass (Qrdm.nbri.5.1; PVE = 17.9%), number of cauline leaves (Qncl.nbri.2.2; PVE = 38.17%) and trichome density (Qtd.nbri.4.1; PVE = 18.9%). Out of these five major QTLs, two (Qbd.nbri.4.3 and Qfd.nbri.4.2) were definitive; however, remaining three QTLs were probable only.

Fig. 4.

Fig. 4

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Diagrammatic representation of linkage map in five chromosomes constructed in the present study. Position and name of markers are given on left and right side of the bar respectively. Different colors of bar given on right side of marker name represent QTLs for different traits identified through single-locus analysis. QTLs represented by dumbbell were detected through two-locus analysis. Mixed linear composite interval mapping was conducted with QTLNetwork 2.1 software to map QTLs with main effect-QTL (M-QTL) and QTLs joint through linear line exhibiting epistatic interactions (E-QTLs) (color figure online)

Table 3.

List of QTLs identified through single-locus analysis for 15 traits

Trait QTL Chr Position Closest marker CI Flanking marker (FM) LOD PVE (%)
Bolting days Qbd.nbri.2.1 2 91.1 29_5738710 80.9–95.5 27_5351360–15_2948517 3.73 6.39
Qbd.nbri.2.2 2 275.2 44_8641585 265.2–291.7 49_9658588–51_10095389 3.09 6.57
Qbd.nbri.2.3 2 382.4 57_11260076 371.3–395.2 59_11632545–65_12709777 3.13 1.54
Qbd.nbri.4.1 4 30 3_558147 20.7–35.7 3_558147–20_3791257 5.41a 8.26
Qbd.nbri.4.2 4 62.4 20_3791257 45.1–69.6 3_558147–25_4695604 3.44 5.45
Qbd.nbri.4.3 4 114.5 1_181227 99.7–118.5 25_4695604–5_929172 6.03a 28.01b
Qbd.nbri.4.4 4 299.2 11_2037232 287.8–310.3 11_2037232–31_5785288 3.74 10.68
Days to flowering Qfd.nbri.4.1 4 26 3_558147 9.4–32 3_558147–20_3791257 4.67a 6.28
Qfd.nbri.4.2 4 113.5 1_181227 95.9–118.5 25_4695604–5_929172 6.26a 25.51b
Qfd.nbri.4.3 4 298.2 11_2037232 284.0–306.6 15_2774125–31_5785288 3.36 8.64
Rosette diameter Qrd.nbri.1.1 1 0 28_8525095 0.0–20.9 28_8525095–1_304565 3.51 6.11
Qrd.nbri.2.1 2 513.4 9_421007 497.3–518.5 72_14156078–75_14752469 3.16 10.58
Rosette leaf length Qrll.nbri.2.1 2 179.5 35_6886284 172.4–185.7 36_7078700–39_7669936 4.22a 9.51
Qrll.nbri.4.1 4 976.3 92_17108224 964.9–981.8 91_16985072–93_17207203 3.19 0.27
Rosette leaf width Qrlw.nbri.1.1 1 488.2 68_20691083 479.6–496.5 65_19770313–67_20380029 3.70 12.9
Qrlw.nbri.2.1 2 320.8 56_11076335 313.0–327.5 53_10435720–55_10846000 3.34 4.38
Qrlw.nbri.2.2 2 429.7 63_12439494 416.4–436.3 8_403972–67_13162265 3.20 9.00
Qrlw.nbri.2.3 2 514.4 9_421007 499.9–519.8 72_14156078–75_14752469 3.02 12.4
No. of rosette leaves Qnrl.nbri.1.1 1 14 28_8525095 0.0–24.8 28_8525095–1_304565 3.21 4.09
Qnrl.nbri.3.1 3 354.9 41_9676804 342.3–366.5 45_10591426–43_10185395 3.08 0.19
Root length Qrl.nbri.1.1 1 52 28_8525095 32.6–62.6 28_8525095–4_1217087 3.39 0.94
Root dry biomass Qrdm.nbri.5.1 5 666.9 76_20483732 660.0–675.6 75_20290025–9_1055153 4.18 17.92b
No of cauline leaves Qncl.nbri.2.1 2 79.4 27_5351360 70.3–87.5 37_7219497–29_5738710 3.84 10.73
Qncl.nbri.2.2 2 134.5 8_1577059 119.3–140.6 13_2561792–12_2345403 4.59 38.17b
Qncl.nbri.2.3 2 672.1 89_17550984 663.1–682.9 91_17990370–100_19684148 3.21 10.90
Cauline leaf length Qcll.nbri.2.1 2 216.1 47_9279156 205.5–228.1 41_8019519–45_8897591 3.00 10.40
Qcll.nbri.2.2 2 716.1 99_19426368 706.8–724.1 100_19684148–96_18940976 3.21 10.91
Qcll.nbri.3.1 3 119.9 15_3534528 109.4–122.2 9_2108626–16_3744536 4.30a 1.73
Qcll.nbri.3.2 3 137.8 17_3942196 126.4–137.8 15_3534528–17_3942196 3.84 1.74
Cauline leaf width Qclw.nbri.3.1 3 118.8 15_3534528 108.0–125.0 9_2108626–16_3744536 3.37 0.59
Trichome density Qtd.nbri.3.1 3 618.7 75_17536522 607.9–633.5 80_18746000–76_17841616 3.33 6.09
Qtd.nbri.4.1 4 146.5 4_759654 131.7–152.3 5_929172–8_1481355 3.89 18.90b
No. of internodes Qni.nbri.4.1 4 1015.9 95_17616992 1002.5–1026.2 93_17207203–100_18583589 3.40 11.39
Internode distance Qid.nbri.1.1 1 293.3 35_10641028 280.2–310.2 32_9737019–37_11253432 3.15 12.07
Plant height Qph.nbri.1.1 1 343.9 41_12471115 332.3–351.9 40_12177865–43_13080079 3.80 9.84
Qph.nbri.2.1 2 254 49_9658588 241.4–258.6 45_8897591–43_8484701 5.19a 9.23
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Major and definitive QTLs are unlined and bold respectively

Chr chromosome, CI confidence interval, PVE phenotypic variation explained

aLOD score more than threshold value to declare definitive QTL

bPVE (%) larger than cut off (15) to declare major QTL

QTL action and identification of dominant and additive effect

The additive and dominant action for individual QTLs is given in Table 4. Out of 36 QTLs, a total of 12 and 24 QTLs showed additive and dominant action respectively. Further, out of 12 additive QTLs, 5 had negative effect and 7 had positive effect. Similarly, out of 24 dominant QTLs, 9 showed negative effect and 15 showed positive effects. No additive QTLs were detected for number of rosette leaves, root length, root dry biomass, cauline leaf width, number of internodes while 3 additive QTLs were identified for cauline leaf length. Eleven QTLs from Col-0 and 25 from Don-0 enhances the trait value (Table 4). Out of 11 QTLs (Col-0 allele positively affect the trait), 2 QTLs of each for number of rosette leaves and cauline leaf length and 1 QTL for each for bolting days, rosette diameter, rosette leaf length, rosette leaf width, root length, cauline leaf width and plant height was detected. Likewise, out of 25 QTLs (Don-0 allele positively affect the trait), 6 QTLs were found to be associated with bolting days; 3 QTLs of each associated with days to flowering, rosette leaf width, and number of cauline leaves; 2 QTLs of each associated with cauline leaf length and trichome density; 1 QTL each associated with rosette diameter, rosette leaf length, root dry biomass, number of internodes, internode distance and plant height.

Table 4.

Additive and dominant effects of QTLs and parental alleles (Col-0 and Don-0) of in individual QTL that enhances corresponding trait

Trait name QTL distribution Chromosome Additive (A) Dominance (D) D/A QTL action Allele that increase trait value
Bolting days Qbd.nbri.2.1 2 0.93 16.76 18.10 D Don-0
Qbd.nbri.2.2 2 1.12 16.61 14.88 D Don-0
Qbd.nbri.2.3 2 − 3.88 16.22 − 4.18 D Col-0
Qbd.nbri.4.1 4 2.67 36.05 13.53 D Don-0
Qbd.nbri.4.2 4 1.90 25.57 13.46 D Don-0
Qbd.nbri.4.3 4 17.78 11.59 0.65 A Don-0
Qbd.nbri.4.4 4 3.94 22.70 5.76 D Don-0
Days to flowering Qfd.nbri.4.1 4 1.23 39.12 31.90 D Don-0
Qfd.nbri.4.2 4 17.92 13.76 0.77 A Don-0
Qfd.nbri.4.3 4 4.18 22.79 5.45 D Don-0
Rosette diameter  Qrd.nbri.1.1 1 1.12 − 0.23 − 0.21 A Col-0
Qrd.nbri.2.1 2 0.66 1.16 1.78 D Don-0
Rosette leaf length  Qrll.nbri.2.1 2 − 0.50 − 0.01 0.01 A Don-0
Qrll.nbri.4.1 4 0.17 − 0.46 − 2.62 D Col-0
Rosette leaf width  Qrlw.nbri.1.1 1 − 0.17 0.14 − 0.82 A Don-0
Qrlw.nbri.2.1 2 0.02 0.24 13.97 D Col-0
Qrlw.nbri.2.2 2 − 0.04 0.25 − 6.58 D Don-0
Qrlw.nbri.2.3 2 − 0.09 0.22 − 2.40 D Don-0
No. of rosette leaves Qnrl.nbri.1.1 1 16.43 − 17.15 − 1.04 D Col-0
Qnrl.nbri.3.1 3 − 7.47 16.32 − 2.18 D Col-0
Root length Qrl.nbri.1.1 1 0.76 − 2.89 − 3.81 D Col-0
Root dry biomass Qrdm.nbri.5.1 5 0.04 0.06 1.43 D Don-0
No. of cauline leaves Qncl.nbri.2.1 2 − 3.69 − 12.77 3.46 D Don-0
Qncl.nbri.2.2 2 − 6.73 − 15.72 2.33 D Don-0
Qncl.nbri.2.3 2 9.44 2.72 0.29 A Don-0
Cauline leaf length  Qcll.nbri.2.1 2 0.22 − 0.17 − 0.77 A Don-0
Qcll.nbri.2.2 2 − 0.19 0.26 − 1.35 D Don-0
Qcll.nbri.3.1 3 0.24 0.21 0.88 A Col-0
Qcll.nbri.3.2 3 0.23 0.20 0.85 A Col-0
Cauline leaf width Qclw.nbri.3.1 3 0.12 0.14 1.17 D Col-0
Trichome density  Qtd.nbri.3.1 3 0.60 − 6.74 − 11.27 D Don-0
Qtd.nbri.4.1 4 5.90 − 2.81 − 0.48 A Don-0
No. of internodes Qni.nbri.4.1 4 0.63 0.91 1.45 D Don-0
Internode distance Qid.nbri.1.1 1 0.29 0.18 0.63 A Don-0
Plant height  Qph.nbri.1.1 1 2.12 5.35 2.52 D Don-0
Qph.nbri.2.1 2 − 6.05 1.46 − 0.24 A Col-0
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QTL identification through epistatic interaction analysis

The epistatic interaction analysis detected a total of 5 QTLs including 1 main effect QTL (M-QTL) and 4 epistatic QTLs (E-QTLs) (Table 5). The M-QTL was associated with bolting days and present on chromosome 4 at 27 cM position (CI = 17–38 cM; closest marker = 3_558147; flanking makers = 3_558147–20_3791257). Out of 4 E-QTL, 2 were identified for rosette diameter (chromosome 3/5 and 4/5) and 1 each for rosette leaf length (chromosome 3/5) and internode distance (chromosome 1/3; Table 5). For E-QTL, PVE ranged from 0.16 to 10.95%.

Table 5.

Summary of epistatic QTLs for three traits identified in two-locus analysis through QTL network

QTL Chr (Position) Flanking markers QTL Chr (Position) Flanking markers AA AD DA DD
Rosette diameter
 Qrd.nbri.3.1 3 (620.7) 80_18746000–75_17536522 Qrd.nbri.5.1 5 (242.2) 21_5657816–24_6445277 0.92 – − 1.92 –
 Qrd.nbri.4.1 4 (473.1) 56_10458272–60_11176263 Qrd.nbri.5.2 5 (242.2) 21_5657816–24_6445277 – 1.67 1.25 1.71
Rosette leaf length
 Qrll.nbri.3.1 3 (640.2) 76_17841616–81_19090024 Qrll.nbri.5.1 5 (233.8) 20_5398815–21_5657816 0.7 – – –
Internode distance
 Qid.nbri.1.2 1 (474.5) 65_19770313–68_20691083 Qid.nbri.3.1 3 (138.1) 17_3942196–19_4458631 0.35 − 0.6 0.33 − 0.53
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AA additive by additive, AD additive by dominance, DA dominance by additive, DD dominance by dominance interactions

Gene identification

The annotation of QTL regions resulted in identification of several previously reported genes such as FRI (FRIGIDA-like protein; AT4G00650), LD (Homeobox protein LUMINIDEPENDENS; AT4G02560), EXGT-A3 (Endoxyloglucan transferase A3; AT2G01850), LPR1 (Low Phosphate Root 1, multi-copper oxidase; AT1G23010), CYTC-1(CYTOCHROME C-1; AT1G22840), PIN7 (Auxin efflux carrier component 7; AT1G23080), CRK (Actin related protein 2/3 complex, subunit 5A; AT4G01710), ATMYC1 (Basic helix-loop-helix DNA-binding superfamily protein; AT4G00480), MYB55 (myb domain protein 55; AT4G01680) and MIR164A (ncRNA, miRNA; AT2G47585). The days to flowering related QTLs region (Qfd.nbri.4.2 and Qfd.nbri.4.3) contains FRIGIDA-like protein (FRI-AT4G00650; Lee et al. 1993) and homeobox protein LUMINIDEPENDENS (LD-AT4G02560; Lee et al. 1994) related to flowering traits. The endoxyloglucan transferase A3 gene responsible for xyloglucan degradation in the differentiating treachery elements of rosette leaves (EXGT-A3-AT2G01850; Campbell and Braam 1999) was found on chromosome 2 near 9_421007 marker of co-localized QTLs for rosette diameter (Qrd.nbri.2.1) and rosette leaf width (Qrlw.nbri.2.3). The QTL region associated with root length (Qrl.nbri.1.1) on chromosome 1 contains 3 genes i.e. CYTC-1 (AT1G22840; Welchen and Gonzalez 2005), LPR1 (AT1G23010; Svistoonoff et al. 2007) and PIN7 (AT1G23080; Nakamura et al. 2004). The root dry biomass related QTL (Qrdm.nbri.5.1) was located on the chromosome 5 that consists of RHD2 gene (respiratory burst oxidase homolog protein C-AT5G51060; Takeda et al. 2008) which determines cell shape in root hair cells. The cauline leaf related QTL (Qcll.nbri.2.2) was also used to study the gene investigation and found MIR164A (AT2G47585) on chromosome 2. The MIR164A was identified for trait associated to cauline leaf length as ncRNA, miRNA which targets CUC2 (modulates the extent of leaf margin serration; Nikovics et al. 2006) and ORE1 (ORE1 to negatively regulate the timing of leaf senescence; Kim et al. 2009). However, 3 genes have been identified for trichome density on chromosome 4 like ATMYC1 (AT4G00480-transcription factor; Urao et al. 1996), MYB55 (putative transcription factor-AT4G01680; Schliep et al. 2010) and CRK (AT4G01710), CRK belongs to the DIS-gene family which encodes actin polymerization factor involved in cell expansion of trichome (Mathur et al. 2003).

Discussion

The selection of parental lines for developing mapping population is an important and crucial step which affects the number as well as the reliability of QTLs detected. The parents with less diversity may suffer with less polymorphism and may lose the chance to identify important QTLs and also undergo inbreeding depression (Zhang et al. 2015). Further, if parental genotypes are distantly related and relationship is too far, it may lead to cross incompatibility as well as segregation distortion of genetic loci (Zhang et al. 2015). Here, we have selected two distinctly and cross compatible ecotypes Col-0 and Don-0 with diversified origin (Cao et al. 2011; Wang et al. 2012). Wide range of morphological variability among the selected parental lines was observed for most of the traits considered during the present investigation (Table 1). Further, the segregation distortion noticed only for 3.2% (11 out of 341) loci suggested that parental genotypes used has balanced genetic relationship and are suitable to develop mapping population for QTL analysis. To the best of our knowledge, no QTL mapping study is available till date using Don-0 and Col-0 although Ler × Don-0 has been used recently (Méndez-Vigo et al. 2016); where flowering time and leaf number traits have been explored. Thus, the present investigation attempted QTL mapping for 15 traits using Col-0 × Don-0 for the first time.

The hybrid vigor noticed for most of the traits in F1 (Supplementary Fig. S2) made us interested to study the dominant effect along with additive effect. The F2 population is considered as most suitable mapping population to study dominant and additive effects simultaneously and have been used in several studies including Arabidopsis (Salomé et al. 2011; Guo et al. 2016; Alhajturki et al. 2018), cowpea (Suanum et al. 2016) and cotton (Kirungu et al. 2018). The identification of 24 (66.6%) and 12 (33.3%) QTLs with dominant and additive effects respectively, confirmed the suitability of F2 population for such kind of study and also might be possible cause for transgressive segregation as reported in different studies (Wang et al. 2007; He et al. 2008). The lower percentage of segregation distortion (3.2%) observed as compared to the previous studies (Méndez-Vigo et al. 2016; Simon et al. 2016) might be due to (1) use of F2 population which has been suggested to less prone to segregation distortion (Zhang et al. 2010), (2) use of intra specific population (Barchi et al. 2010), and (3) use of co-dominant (SNP) markers (Zhang et al. 2015). Further, there are varying views about the utilization of loci with segregation distortion in linkage mapping. Removal of distorted loci could lead to loss of information in terms of genetic coverage and identification of QTLs. However, inclusion of distorted loci could lead to biased mapping on chromosome and also distance between loci. Out of total 36 QTLs, 7 and 5 QTLs were found to be definitive and major, respectively. For instance, we have mined 2 bolting days QTLs (Qbd.nbri.4.3 and Qbd.nbri.4.1) with high LOD and PVE on chromosome 4 and might be considered as unique allele/candidate gene for bolting days. Three QTLs were also identified for days to flowering on chromosome 4. Similarly, previous studies also reported QTLs on chromosome 4 using different combination of Arabidopsis ecotypes (Kover et al. 2009; Huang et al. 2011; Alhajturki et al. 2018). The comparative analysis indicates the accuracy of present developed mapping population. Moreover, we have detected QTLs for rosette diameter and leaf length located on the chromosome 2 indicating that this chromosome might have important loci controlling rosette traits. New QTLs for leaf width was also identified on the chromosome 1, 2 and 3 in the present study (5 QTLs) which would be interesting for further dissection of this trait. The root traits related QTLs detected on the chromosome 1 (Reymond et al. 2006) and root related genes were also detected within the same region. In addition to that, two transcription factor (MYB55: AT4G01680 and AtMYC1: AT4G00480) were explored within identified trichome density associated QTL region on chromosome 4. Two novel QTLs were detected for internode on chromosome 1 and 4 as there is no previous report for this trait. Further study of these chromosomal regions would be quite interesting for extraction of internode related novel genes/alleles in Arabidopsis.

The identification of only few QTLs for some traits suggested that some important genomic regions remains un-captured and needs to be explored further with more number of markers. The Don-0 ecotype enabled us to identify several novel alleles that played important roles to control different traits of Arabidopsis (Méndez-Vigo et al. 2016) due to presence of unique SNPs (Cao et al. 2011). Seven definitive QTLs identified for five traits (bolting days, days to flowering, rosette leaf length, cauline leaf length and plant height) provide more confidence, however, remaining probable QTL (29) could not be ignored since they have also been identified with good LOD score (> 3.0). Previously, epistatic interactions have been studied in Arabidopsis to understand the trait genetics (Mojica et al. 2016). During the present investigation, we also identified epistatic QTLs (E-QTLs) for rosette diameter, rosette leaf length and internode distance, and some QTLs for same or different traits were co-localized. The co-localized QTLs have been detected for several traits in Arabidopsis (Mojica et al. 2016; Meyer et al. 2016) and other crops like wheat (Horn et al. 2016), cowpea (Suanum et al. 2016), and maize (Wang et al. 2016). The co-localization might occur due to pleiotropy or tight linkage between QTLs (Breseghello and Sorrells 2007; Das et al. 2012). Another possible reason of co-localized QTLs could be the use of F2 mapping population with limited population size which resulted into poor resolution (Zhang et al. 2015), thus co-localized QTLs must be examined further with other mapping population like recombinant inbred lines (RILs) with more population size for validation. The co-localized QTLs have also been observed in Ler × Col, Cvi × Ler derived population (Ungerer et al. 2002) for number of traits. Interestingly, the identification of multiple QTLs for multiple traits were comparable to a previous study (Ungerer et al. 2002), which suggested that the chromosome 2 may have QTL hot spot.

The genes identified within the QTLs regions includes LPR1 gene on chromosome 1 for root trait (Low Phosphate Root-1 located in endoplasmic reticulum and adjusts root meristem activity) and validated in Bay-0 × Shahdara mapping population (Svistoonoff et al. 2007; Reymond et al. 2006). The flowering related genes FRI and LD were detected within flowering associated QTL on chromosome 4 which confirms the contribution of these well characterized genes and existence of other un-identified new region or loci for flowering (Méndez-Vigo et al. 2016; Salomé et al. 2011). The CRK and AtMYC1 locus-Transcription factor related to trichome density were also identified on chromosome 4 which controls the trichome development (Schwab et al. 2003; Symonds et al. 2011). In addition, there was one miRNA identified on chromosome 2 named MIR164A which targets CUC2 (CUP-SHAPED COTYLEDON 2, NAC family of transcription factors) and regulates leaf serration in Arabidopsis (Nikovics et al. 2006; Huang et al. 2011). Parental diversity for leaf margin (Col-0: serrate leaf margin, Don-0: smooth leaf margin; Fig. 1) may be regulated by MIR164A. There were some QTLs in which genes were not identified but we can predict that there must be some important chromosomal region or loci (genes and their upstream or downstream region) which governs the particular trait in cis or trans pattern. These comparative results and depth genomic region study verified the reliability and accuracy of identified QTLs in the present investigation i.e. QTLs and related genes were found within same chromosomal region for respective trait. This needs further investigation through fine mapping for tracking the region of QTLs associated with desired traits. The novel QTLs identified in this analysis may be useful to identify unique and desirable variants of gene in future studies due to presence of unique SNPs and more active alleles of Don-0 (Wang et al. 2012; Méndez-Vigo et al. 2016) for selected traits.

Conclusion

The present study identified several QTLs using Col-0 × Don-0 derived mapping population. Some of these QTLs confirmed the association of novel genomic region or related genes with traits. The identified QTLs provides better insights into genetic architecture of traits in addition to current knowledge. The dominant effect QTLs may prove to be useful to develop hybrid with enhanced trait that may further be utilized to explore genes with dominant and over-dominant effects. The present study is needed because of unique genetic makeup of Don-0 which may create some new alleles through hybridization with Col-0 due to recombination event. Several novel QTLs has been identified for desired traits for the first time, for example rosette leaf traits (rosette diameter, leaf length and width), cauline leaf traits (number, length and width), internode traits and trichome density. However, new allele may be present in common QTL region for same or different traits, therefore in-depth analysis will allow to tag elite genes/loci. Further analysis of major QTLs (bolting days, days to flowering, root dry biomass, number of cauline leaves, trichome density) could be utilized to characterize the novel genes through fine mapping and map based cloning. Since Arabidopsis is considered a model plant, the identified QTLs may also be utilized to identify gene/QTLs in other crops through comparative genomics.

Electronic supplementary material

Below is the link to the electronic supplementary material.

12298_2020_800_MOESM1_ESM.pptx (2.7MB, pptx)

Table S1 Chi square test for Mendelian segregation in F2 population using 341 markers (PPTX 2750 kb)

12298_2020_800_MOESM2_ESM.pptx (4MB, pptx)

Fig. S1 Snapshot from Sequenom MassArray showing as an example of one SNP (Chr4_SNP_6_764109) data of Col-0, Don-0 and their hybrid. Col-0, Don-0 represents homozygous call of C-allele and A –allele respectively. Hybrid shows heterozygous call (both C-allele and A–allele) (PPTX 4119 kb)

12298_2020_800_MOESM3_ESM.xlsx (22.5KB, xlsx)

Fig. S2 Comparative phenotypes of Col-0 (left), Hybrid (middle) and Don-0 (right), plant height (A); rosette leaf (B); trichome density (C); cauline leaf and internode (D) (XLSX 22 kb)

Acknowledgements

This research was financially supported by Council of Scientific and Industrial Research (CSIR), India (BSC 0204). All the experiments and analysis was performed at CSIR-National Botanical Research Institute (NBRI), Lucknow. The authors also thank Late Dr. SA Ranade, Chief Scientist and Dr. KN Nair, Senior Principal Scientist, NBRI for helpful suggestions.

Author contributions

The experiment was designed by S.V.S. and H.K.Y. Experiments were conducted by A.G, and data analysis performed by A.G. and V.J. All the authors have read and approved the final manuscript.

Compliance with ethical standards

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Samir V. Sawant, Email: samirsawant@nbri.res.in

Hemant Kumar Yadav, Email: h.yadav@nbri.res.in.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

12298_2020_800_MOESM1_ESM.pptx (2.7MB, pptx)

Table S1 Chi square test for Mendelian segregation in F2 population using 341 markers (PPTX 2750 kb)

12298_2020_800_MOESM2_ESM.pptx (4MB, pptx)

Fig. S1 Snapshot from Sequenom MassArray showing as an example of one SNP (Chr4_SNP_6_764109) data of Col-0, Don-0 and their hybrid. Col-0, Don-0 represents homozygous call of C-allele and A –allele respectively. Hybrid shows heterozygous call (both C-allele and A–allele) (PPTX 4119 kb)

12298_2020_800_MOESM3_ESM.xlsx (22.5KB, xlsx)

Fig. S2 Comparative phenotypes of Col-0 (left), Hybrid (middle) and Don-0 (right), plant height (A); rosette leaf (B); trichome density (C); cauline leaf and internode (D) (XLSX 22 kb)

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