Quantitative Trait Loci Mapping for Theobromine and Caffeine

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Omics Technologies Applied to Agriculture and Food

Quantitative Trait Loci Mapping for Theobromine and Caffeine Contents in Tea Plant (Camellia sinensis) Jian-Qiang Ma, Ji-Qiang Jin, Ming-Zhe Yao, Chun-Lei Ma, Yan-Xia Xu, Wan-Jun Hao, and Liang Chen J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.8b05355 • Publication Date (Web): 28 Nov 2018 Downloaded from http://pubs.acs.org on November 30, 2018

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Journal of Agricultural and Food Chemistry

Quantitative Trait Loci Mapping for Theobromine and Caffeine Contents in Tea Plant (Camellia sinensis) Jian-Qiang Ma#, Ji-Qiang Jin#, Ming-Zhe Yao, Chun-Lei Ma, Yan-Xia Xu, WanJun Hao, Liang Chen* Key Laboratory of Tea Plant Biology and Resources Utilization, Ministry of Agriculture, Tea Research Institute of the Chinese Academy of Agricultural Sciences (TRICAAS), 9 South Meiling Road, Hangzhou 310008, China #Authors *E-mail:

contributed equally to this work. [email protected]. Phone: +86 571 86652835. Fax: +86 571

86653866.

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ACS Paragon Plus Environment


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Abstract

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Understanding the genetic basis of theobromine and caffeine accumulation in

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the tea plant is important due to their contribution to tea flavor. In this study,

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quantitative trait loci (QTL) analyses were carried out to identify genetic variants

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associated with theobromine and caffeine contents and ratio, using a pseudo-

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testcross population derived from an intervarietal cross between two varieties of

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Camellia sinensis. A total of ten QTL controlling caffeine content (CAF),

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theobromine content (TBR), sum of caffeine and theobromine (SCT), and caffeine-

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to-theobromine ratio (CTR) were identified over four measurement years. The

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major QTL controlling CAF, qCAF1, was mapped onto LG01 and validated across

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years, explaining an average of 20.1% of the phenotypic variance. The other QTL

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were detected in one or two years, and of them there were four, two and three for

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TBR, SCT and CTR, respectively. The present results provide valuable information

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for further fine mapping and cloning functional genes, and for genetic improvement

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in tea plant.

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Keywords: tea plant, caffeine, theobromine, quantitative trait loci

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INTRODUCTION

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Tea is one of the most popular non-alcoholic beverages, made by infusing of

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processed tender shoots of tea plant (Camellia sinensis) and related species, which

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all belong to the section Thea of the genus Camellia in the family Theaceace. These

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plants have been utilized more than two thousand years in China where they were

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originally used for traditional medicine and subsequently for food and drinking.

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Recent research on phytochemical analysis of tea extracts have identified many

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bioactive compounds, such as flavonoids, methylxanthines, L-theanine and

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polysaccharides. 1-6 These versatile natural metabolites have not only contributed to

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the unique taste and flavor of tea, but also proved to have powerful health-promoting

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effects,7-10 which raises a growing interest and consumption of tea and relative

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products containing tea constituents.

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Methylxanthines are a group of purine-like alkaloids.11-13 Caffeine (1,3,7-

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trimethylxanthine) and theobromine (3,7-dimethylxanthine) are the major

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methylxanthines accumulated in the tea plant, contributing up to about 6% of the

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dry weight of ‘two and a bud’ (i.e. the apical bud and two adjacent leaves harvested

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for tea producing).14-16 Caffeine had a wide range of beneficial effects, such as

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central nervous system stimulation, diuresis and cardiovascular function, while

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theobromine has similar but less biological activity.2,17 Caffeine and theobromine

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are bitter tastants which elicit bitterness through a family of TAS2R receptors,18-20

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playing an important role on tea flavor.21-24 For example, the previous studies

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showed caffeine was the main contributor to bitterness in green tea.25-30 Scharbert

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and Hofmann31 demonstrated caffeine was as one of the key bitter compounds in

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black tea. Pérez-Burillo et al.32 found a high correlation between caffeine and

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bitterness in white tea. Furthermore, the interaction of caffeine and flavonoids

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increased the intensity of bitterness and astringency in tea infusion.22,26,31 Therefore,

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understanding the genetic basis of caffeine and theobromine accumulation in the tea

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plant is important for breeding efforts to improve tea quality.33-36

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Previous investigations have proved theobromine and caffeine are products of

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purine metabolic pathway in tea plant.11-13 The main biosynthetic route is

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xanthosine→ 7-methylxanthosine → 7-methylxanthine → theobromine → caffeine.

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The three methylation steps are catalyzed by the N-methyltransferases (NMTs),

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using S-adenosyl-L-methionine (SAM) as the methyl donor. The tea caffeine

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synthase 1 (TCS1), a bifunctional NMT with both 1-N- and 3-N-methylation

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activity, plays a crucial role in the biosynthesis of theobromine and caffeine.37 The

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studies we conducted recently revealed that the tea germplasms containing specific

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TCS1 alleles with low transcription level or enzymatic activity of encoded proteins

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showed less caffeine accumulation than those with normal alleles.38,39 However, the

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contents of theobromine and caffeine are a complicated quantitative trait affected

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by both genetic and environmental factors, and to date, there is still limited

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information defining the underlying genetic mechanism.

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In this study, we used an F1 full-sib family to investigate the genetic basis of

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variation for theobromine and caffeine accumulation in the tea plant through

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quantitative trait loci (QTL) mapping of four associated traits, i.e. caffeine content

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(CAF), theobromine content (TBR), sum of caffeine and theobromine (SCT), and

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caffeine-to-theobromine ratio (CTR). The findings will help to elucidate the

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molecular mechanism controlling theobromine and caffeine accumulation and to

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accelerate the genetic improvement of tea plant.

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MATERIALS AND METHODS

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Mapping population. An F1 pseudo-testcross population was generated by

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crossing C. sinensis var. sinensis ‘Yingshuang’ (‘YS’) and C. sinensis var.

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pubilimba ‘Beiyue Danzhu’ (‘BD’). The population composed of 148 individuals

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was genotyped using 406 simple sequence repeats (SSR) and 6042 SNP markers for

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genetic map construction. Details were fully described in the previous studies.40

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Phenotypic data collection. Field experiments were conducted at the

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Experimental Station of TRICAAS as described previously.40,41 In briefly, each

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parent and progeny were clonally propagated and grown in a randomized complete

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block design with three replications. The ‘two and a bud’ of first flush in the spring

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were harvested and dried for phytochemical analysis using high performance liquid

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chromatography (HPLC) in 2010, 2011, 2014 and 2015.

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The HPLC method was carried out following the international standard ISO

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14502-2:2005 with minor modifications. Firstly, a 0.2 g of dry ‘two and a bud’

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powder was extracted twice in the 70 °C water bath for 10 minutes using 5 mL 70%

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methanol. The supernatant was collected and made up the volume to 10 mL with 70%

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methanol. Then 1 mL of the supernatant was diluted to 5 mL with stabilizing

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solution (10% v/v acetonitrile, 500 mg/mL EDTA and ascorbic acid), and

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subsequently filtered through a hydrophilic nylon membrane filter with a 0.45 µm

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pore size. Afterwards, the solution was detected using HPLC-UVD (Waters 2695-

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2489) with a SunFire C18 column (5 µm, 4.6 mm × 250 mm, Milford, MA, USA ).

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The mobile flow rate was 1.0 mL/min, and column oven temperature maintained at

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35 °C. Solvents were (A) 1% v/v formic acid and (B) acetonitrile. A binary gradient

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elution system was performed as follow: 93.5 to 85% A (0-16 min), 85 to 75% A

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(16-20 min), 75.0 to 93.5% A (20-26 min), isocratic 93.5% A (26-30 min). Spectral

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data were collected at 280 nm wavelength. The chromatographic peaks of caffeine

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and theobromine were identified by comparing the retention times of reference

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substances. Calibration curves for quantification were generated by plotting the

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peak area against the known concentration of reference substance.

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Phenotypic data analysis.

Statistical analyses of phenotypic data were

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conducted using PASW Statistics version 18.0 (IBM SPSS Inc., Chicago, IL, USA).

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The significant differences between the mean values of parental traits were analyzed

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using t-test. The mean, standard deviation (SD), coefficient of variation (CV),

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kurtosis and skewness in the F1 population were calculated for each trait. Pearson's

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correlations were estimated using the combined datasets over years. Variance

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components were calculated using multi-factor analysis of variance. The years of

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phenotypic data collection were considered as different environments, and

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heritability was estimated as variance among genotypes divided by the total of

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genotypes, genotype-by-environment interaction and residual variances.

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QTL analysis. Linkage map information was described in the previous

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studies.40 QTL mapping was performed using MapQTL 6 with the combination of

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interval mapping (IM) and restricted multiple QTL model (rMQM) methods.42

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Logarithm of odds (LOD) threshold for QTL declaration was estimated for each

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trait and year using a permutation test (1,000 replications). The location of

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maximum LOD score exceeded the genome-wide significance threshold of 95%

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somewhere on the linkage group was considered as the position of the QTL, and the

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region with a LOD score greater than the threshold was considered as the confidence

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interval. The QTL detected across years for each trait was assigned to be the same

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stable QTL if confidence intervals overlapped, and QTL with over 10% of

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phenotypic variance explained (PVE) was defined as the major QTL.

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RESULTS AND DISCUSSION

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Phenotypic variation. The phenotypic values of the traits measured of the

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parents and F1 population over four years are shown in Table 1. The two parents

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significantly differed in all traits investigated. The paternal parent ‘BD’ had higher

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CAF, TBR and SCT, but lower CTR than the maternal parent ‘YS’. The overall

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averages of CAF, TBR, SCT and CTR across years were 33.9 mg▪g-1, 6.7 mg▪g-1,

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40.6 mg▪g-1 and 6.0 for ‘YS’, while 41.0 mg▪g-1, 10.4 mg▪g-1, 51.4 mg▪g-1 and 4.6

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for ‘BD’, respectively. The previous investigation of the representative Chinese tea

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germplasms revealed that there was a high level of variation in CAF and TBR, with

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a range from 2.3 to 53.4 mg▪g-1 and 0.5 to 46.7 mg▪g-1, respectively.14 Meanwhile,

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the three varieties of C. sinensis was significantly different in CAF, and generally

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the varieties of C. sinensis var. pubilimba and var. assamica had a higher CAF than

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var. sinensis.14 The maternal parent ‘YS’ was developed from the progeny by

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crossing the sinensis and assamica varieties, and hence had an average level of CAF

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and TBR. In comparison, the paternal parent ‘BD’, a germplasm of the pubilimba

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variety, showed a slightly higher CAF and TBR.

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A continuous distribution with transgressive bidirectional segregation was

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observed among the F1 population for all traits, and which indicated quantitative

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genetic architecture (Figure 1). The phenotypic values within the progeny across

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years varied from 21.3 to 49.0 mg▪g-1 for CAF, 4.2 to 16.1 mg▪g-1 for TBR, 29.1 to

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55.5 mg▪g-1 for SCT, and 1.7 to 25.4 for CTR, respectively (Table 1). The mean

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values were slightly smaller than the corresponding mid-parent values for all traits,

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with the exception of CTR. The population coefficient of variation (CV) for TBR

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and CTR was considerably higher than that for CAF and SCT. The high level of

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genetic variation among the progeny for the aforesaid traits suggested that

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significant improvements can be achieved through hybridization and selection.

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The Pearson correlations between each trait over years are presented in Table

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2. CAF and TBR showed a significant negative correlation (r = -0.466, p < 0.001).

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SCT was more highly correlated with CAF (r = 0.681, p < 0.001) than with TBR (r

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= 0.330, p < 0.001). CTR showed a significant positive correlation with CAF (r =

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0.550, p < 0.001), and a significant negative correlation with TBR (r = -0.860, p

Quantitative Trait Loci Mapping for Theobromine and Caffeine

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