Abstract
Anthocyanins are important molecules that are responsible for fruit color formation and are also beneficial to human health. To date, numerous structural and regulatory genes associated with anthocyanin biosynthesis in peach (Prunus persica) have been reported based on linkage analysis. In this study, we sought to identify further genes associated with anthocyanin content in peach by conducting a genome-wide association analysis of 129 peach accessions to detect markers associated with the trait. Significant association signals were detected when anthocyanin content was considered a qualitative character but not when it was considered a quantitative trait. We detected an association region located between 11.7 and 13.1 Mb in chromosome 1, a region in which only 133 of 146 genes have previously been functionally annotated. Gene ontology annotation of the genes in this region showed that membrane-associated genes (including one gene encoding a chloride channel protein and 17 sugar transport/carrier-associated genes) were significantly enriched, and we focused on these in subsequent analyses. Based on in vitro induction of anthocyanins in fruit flesh using different exogenously applied sugars and subsequent culture, we found that the expression level of 3 of the 18 membrane-associated genes, Prupe.1G156300, Prupe.1G156900, and Prupe.1G157000, increased during induction treatment. Furthermore, during the fruit development period of a white-fleshed and a red-fleshed peach cultivar, the expression of one gene encoding a transmembrane sugar transport protein was observed to be positively correlated with anthocyanin biosynthesis. These results will facilitate understanding of the molecular mechanism of anthocyanin biosynthesis in peach.
Anthocyanins are important pigments in plants. These compounds are found in stems, leaves, petals, and flesh of fruit (Forkmann and Martens, 2001; Gould et al., 2009), and play important roles in attracting insect pollinators and animal seed dispersers, and in disease and insect resistance, like fungi, herbivores, cold, and excess radiation (Chalker, 2002, 2010; Karageorgou and Manetas, 2006). For example, anthocyanins can absorb visible light without participating in photosynthesis; their presence in leaves should reduce the probability of photon capture by chlorophylls, thereby lowering photosynthesis (Karageorgou and Manetas, 2006). Anthocyanins also are beneficial to human health, and it has been found that foods with high anthocyanin content reduce free radicals, promote blood circulation, prevent cardiovascular and cerebrovascular diseases, and also have antiaging and anticancer properties (Chen et al., 2006; Choi et al., 1997; Xia et al., 2010). Yang et al. (2018) found that anthocyanins from purple wheat (Triticum aestivum) can inhibit the infection capacity and proliferation of hgc-27 and mgc-803 gastric cancer cells. Lila et al. (2016) argued that anthocyanins undergo enterohepatic recycling in the human body, leading to prolonged residence time, and thus enhanced bioavailability; however, levels were found to be very low in routine blood samples taken after ingestion. Single oral administration of anthocyanin has been demonstrated to reduce smoking-induced endothelial dysfunction in young healthy smokers (Akane et al., 2018), whereas cyanidin-3-O-glucoside also can alleviate the Pb-induced decrease in progesterone biosynthesis to reduce the toxicity of heavy metals in rat Leydig cells, and anthocyanin is able to chelate heavy metals and reduce metal ion concentrations, thereby further alleviating heavy metal–induced toxicity (Wen et al., 2018; Zhou et al., 2017).
Peach, a member of the Rosaceae family native to China, is among the four most widely cultivated fruit tree species worldwide (Tuan et al., 2015), and serves as a model for genetic studies owing to its small genome size of 265 Mb (Dirlewanger et al., 2004; Shulaev et al., 2008; Zhu et al., 2012), and the whole-genome sequence of peach has been released (Verde et al., 2013), providing an important foundation for the genome-wide identification of genes in this species (Verde et al., 2017). Typically, peach has one of two types of flesh color: white or yellow. After studying the anthocyanin pigments in peaches, research found that there were two main pigments in peach, cyanidin-3-glucoside and cyanidin-3-rutinoside, with the former content being ≈10 times more than the latter. In addition, no clear differences were observed in pigment contents of white and yellow flesh accession (Tomas-Barberan et al., 2001). In recent decades, peaches with red flesh have attracted the attention of a large number of researchers worldwide (Ding, 2017).
To date, candidate genes involved in biosynthesis, regulation, and response to induction by environmental stimuli, such as light, and temperature, and sugar and plant hormones, have been identified in peach (Donoso et al., 2016; Eduardo et al., 2011; Frett et al., 2014; Jaakola, 2013; Jiao et al., 2014; Rahim et al., 2014; Zhou et al., 2017). Among the biosynthetic genes identified, there are a number of structural genes that directly encode enzymes required for the biosynthesis of anthocyanin, including chalcone synthase (CHS), chalcone isomerase, leucoanthocyanidin dioxygenase/anthocyanidin synthase, and UDP-glucose flavonoid 3-O-glucosyltransferase (UFGT) (Tsukaya, 2004). It is currently believed that the process of anthocyanin biosynthesis is mainly regulated by three classes of transcription factors, namely, v-myb avian myeloblastosis viral oncogene homolog (MYB), basic helix-loop-helix (bHLH), and tryptophan-aspartic acid 40 (WD40) transcription factors (Xu et al., 2015). Among these, MYB transcription factor genes often are found to be the major determinant of anthocyanin accumulation by acting in conjunction with bHLH and WD40 proteins to activate key anthocyanin biosynthetic genes (Allan et al., 2008; Lin-Wang et al., 2010; Petroni and Tonelli, 2011). The major transcription factor R2R3 MYB10/MYB1/MYBA was shown to be associated with activation of the anthocyanin biosynthesis pathway in the Rosaceae (Allan et al., 2008; Lin-Wang et al., 2010), leading to the development of red flesh pigmentation, and is located within the interval of the major markers associated with blush on linkage group 3 (Frett et al., 2014). However, Zhou et al. (2015) found that the sequence of PpMYB10.1 did not segregate along with the red flesh phenotype, although their team identified another gene, a NAC transcription factor gene (PpBL), that was significantly differentially expressed between the red- and white-fleshed cultivars and confirmed that this gene could affect anthocyanin biosynthesis by regulating PpMYB10.1 using transient transformation of tobacco (Nicotiana benthamiana) and peach (Zhou et al., 2015). Recently, Cao et al. (2018) identified 66 genes were significantly correlated with anthocyanin contents through RNA-sequencing (RNA-seq), 22 of which previously reported as regulatory, biosynthetic, and transporter genes, including PpMYB and PpBL, are involved in the regulatory network of anthocyanins. Unfortunately, no polymorphic sites have been identified in the coding sequence of the genes in red-fleshed peach. More research is needed to locate key genes involved in red flesh traits in peach.
Genome-wide association study (GWAS) has proved to be a useful tool for dissecting the genetic locus of complex agronomic characters in arabidopsis (Arabidopsis thaliana), rice (Oryza sativa), maize (Zea mays), wheat, and barley (Hordeum vulgare) (Gyawali et al., 2017; Kim et al., 2016; Revilla et al., 2016; Togninalli et al., 2018; Turuspekov et al., 2017). It has the advantage of not requiring prior establishment of a mapping population and can detect multiple allele loci, thereby saving both time and labor. In peach, Cao et al. (2012) demonstrated GWAS analysis to be an effective complement to traditional quantitative trait locus mapping.
In this study, we performed a GWAS with the aim of locating the region associated with anthocyanin content in peach flesh. Candidate genes were identified based on an in vitro experiment involving sugar induction of fruit flesh and comparing these genes at different stages of fruit development. The findings of this study provide a more comprehensive understanding of the molecular mechanisms underlying anthocyanin biosynthesis and could be useful in development and application of molecular markers for peach breeding.
Materials and Methods
Plant materials.
Three sources of plant materials were used in this study, the first of which was 129 peach accessions previously used in GWASs (Cao et al., 2016; Supplemental Table 1). For each of these cultivars, fresh samples of the mesocarp of three ripe fruit were mixed and frozen in liquid nitrogen and then stored at −80 °C for anthocyanin evaluation. In addition, total DNA was extracted from the fresh leaves of these accessions for genome re-sequencing.
The second source of material was the flesh of ‘Tianjin Shui Mi’ peach fruit harvested at 15 d before fruit maturity (the key stage of anthocyanin accumulation, 80 d after blooming). The flesh of the harvested fruit was cultured in the presence of exogenous sugar for candidate gene screening. The ripe stage was evaluated according to the grading standards described by Zhang (2008).
The third source of material was two peach accessions with different anthocyanin contents, a white-fleshed peach (‘Hakuho’) and a red-fleshed peach (‘Tianjin Shui Mi’), in which anthocyanin accumulates during the late stage of fruit development (Ding, 2017). The maturation periods of these accessions are all early July in Zhengzhou, China. Three fruit of each cultivar were harvested at three stages, from which three replicate fresh samples were analyzed separately.
Anthocyanin quantification in fruit flesh.
We used a high-performance liquid chromatography system (HPLC; Shimadzu Corp., Kyoto, Japan) coupled with photodiode array detector to analyze flesh anthocyanin contents 1 cm depth from surface of 129 peach accessions at mature time, which are characterized by different flesh colors, and also in two accessions during different fruit development periods, and in sugar-induced fruit with different treated times. Accurately weighed samples (1 g) of powdered fruit flesh were placed into 50-mL flasks containing 25 mL of a methanol/formic acid/water (45:1:4 v/v/v) mixture and incubated overnight (12 h) at 4 °C. Following centrifugation at 2000 gn, the supernatant was collected and used for HPLC analysis to evaluate cyanidin-3-glucoside and cyanidin-3-rutinoside. The injection volume was 20 μL, the flow rate was 1 mL·min−1, and the detection wavelengths were 280 and 516 nm. A standard curve was prepared using cyanidin-3-O-glucoside as a standard sample. In addition, anthocyanin content was phenotyped in 2014 and 2015 as a qualitative character based on previously published plant genetic resources’ evaluation criteria (Wang and Zhu, 2005). In the book, red pigment can be classified into two types according to some reference cultivars.
Genome-wide association study.
Three models of Tassel v4.0 software (Bradbury et al., 2007) were used to perform GWAS based on the previously identified single-nucleotide polymorphisms (SNPs) of 129 peach accessions (Cao et al., 2016). The first model was general linear model (GLM) without any consideration for principal component analysis (GLM–no PCA); the second was GLM but took PCA results into account as the fixed effect (GLM-PCA); and the third was a mixed linear model (MLM) using PCA results and the kinship as correction for population structure. In the model, a kinship matrix was calculated using Tassel software and the first three components of PCA were determined using genome-wide complex trait analysis (GCTA) (Yang et al., 2011). Manhattan and quantile-quantile plots were generated using the qqman package in R (Turner, 2014), according to the association results for anthocyanin. We defined a whole-genome significance cutoff from the Bonferroni test threshold (significant genome-wide threshold: −log10 P = 8.49, calculated by dividing 0.01 using 3,076,604 SNPs). Gene ontology (GO) annotations of candidate genes were performed using Blast2GO (Conesa and Gotz, 2008) and plotted using WEGO (Web Gene Ontology Annotation Plot) (Ye et al., 2006).
In vitro induction of anthocyanin synthesis by sugar.
A red-fleshed peach ‘Tianjin Shui Mi’ was selected to conduct this experiment. The flesh was cut into small pieces (2 × 2 × 2 mm) during the stage of development at which the flesh color changes (≈15 d before the date of maturity). These samples were incubated in 2-(N-morpholino)ethanesulfonic acid (MES) culture medium (pH = 6.5), containing 100 mm MES (pH 5.5), 5 mm CaCl2, 10 mm MgCl2, 1 mm EDTA, 10 mm vitamin C, and 100 mm sugar (glucose, sucrose, fructose, or sorbitol), at room temperature (25 °C). The incubation method was consulted from a previous study (Beruter and Studer Feusi, 1995; Do and Cormier, 1990; Jia, 2013) and adjusted a little. Light was supplied by fluorescent lamps with 62.5 μmol·m−2·s−1 for 24 h. As a control, flesh was incubated in each MES medium containing mannitol to balance the osmotic potential. After treatment for 0, 12, and 24 h, flesh samples were frozen in liquid nitrogen and stored at −80 °C for subsequent RNA extraction and anthocyanin evaluation.
Transcriptional analysis of fruit flesh induced by sugar.
Total RNA (2 µg) was extracted of the induced fruit flesh using a Quick RNA Isolation Kit (Waryong, Beijing, China) according to the manufacturer’s instructions. Purification of poly (A) messenger RNAs (mRNAs) was performed using oligo-dT attached to magnetic beads. The purified mRNAs were fragmented using ultra-sonication, and then subjected to first- and second-strand complementary DNA (cDNA) synthesis using random hexamer primers. Thereafter, cDNA fragments of ≈350 base pairs (bp) in size were gel-purified and used as templates in a polymerase chain reaction (PCR) and sequenced using a high-throughput sequencing platform (BGISEQ-500; GitHub, Shenzhen, China). Finally, the sequencing data were filtered using SOAPnuke (GitHub, 2016) and aligned against the peach reference genome v2.0 (Verde et al., 2017) for better annotation comparison of v1.0. Gene expression was calculated in terms of reads per kilobase per million mapped reads using Cufflinks v2.1.1 (Trapnell et al., 2010).
Real-time quantitative PCR.
Fruit of the third source of material was used for extraction of RNA using an RNA extraction kit (EASYspin Plus; Aidlab, Beijing, China), and its purity was evaluated using a spectrophotometer (NanoDrop 1000; Thermo Fisher Scientific, Waltham, MA). cDNA was synthesized from 2 μg of RNA using a First Strand cDNA Synthesis Kit (ReverTra Ace-α-FSK101; Takara, Dalian, China) according to the manufacturer’s protocol. According to gene sequences annotated by Verde et al. (2017), specific primers for three genes (Table 1) were designed using Primer-BLAST software (National Center for Biotechnology Information, Bethesda, MD).
Details of primers used for quantitative real-time polymerase chain reaction to amplify genes related to sugar metabolism in peach fruit flesh.
Real-time quantitative PCR reactions were performed using the fluorescent quantitative PCR instrument (LightCycler 480; Roche Diagnostics, Mannheim, Germany) with a 10-μL reaction mixture containing 10 ng cDNA, 0.5 mm of each primer, 5 μL Premix Taq solution (Takara), and 3.5 μL double distilled water. The real-time quantitative PCR reaction program used was as follows: 95 °C for 5 min; followed by 35 cycles of 94 °C for 30 s, the annealing temperature for 30 s, and 72 °C for 30 s; with a final elongation for 10 min at 72 °C. Relative expression levels were estimated using the comparative Ct method (Livak and Schmittgen, 2001). The sequences of the primers used in this study are shown in Table 1.
Results
Anthocyanin phenotyping.
The anthocyanin contents of 129 peach cultivars in 2014 (Fig. 1A and B) revealed cyanidin-3-glucoside but cyanidin-3-rutinoside as the primary component of anthocyanin, therefore we focused on this molecule in the subsequent analyses in 2014 and 2015 (Fig. 1A and C). Forty-eight of the assessed cultivars were found to be lacking in all anthocyanin evaluation, whereas among the remainder, cyanidin-3-glucoside showed skewed distribution (Fig. 1A and C). Most of these latter accessions had anthocyanin concentrations ranging between 0 and 10 mg·kg−1 of fresh fruit, whereas only ≈10 cultivars showed higher concentrations. However, we detected no segregation distortion when the anthocyanin concentrations trait was considered as a qualitative character by direct observation (Fig. 1D).
Anthocyanin quantification in fruit of 129 peach accessions in (A and B) 2014, (C) in 2015, and (D) classification. FW = fresh weight.
Citation: Journal of the American Society for Horticultural Science J. Amer. Soc. Hort. Sci. 144, 3; 10.21273/JASHS04622-18
Anthocyanin quantification in fruit of 129 peach accessions in (A and B) 2014, (C) in 2015, and (D) classification. FW = fresh weight.
Citation: Journal of the American Society for Horticultural Science J. Amer. Soc. Hort. Sci. 144, 3; 10.21273/JASHS04622-18
Anthocyanin quantification in fruit of 129 peach accessions in (A and B) 2014, (C) in 2015, and (D) classification. FW = fresh weight.
Citation: Journal of the American Society for Horticultural Science J. Amer. Soc. Hort. Sci. 144, 3; 10.21273/JASHS04622-18
Sequencing and GWAS.
In the study, we identified 4,062,178 SNPs in 129 peach cultivars. After filtering the data using a minor allele frequency threshold of ≤ 0.05 and absent in more than 20% assessed cultivars, finally, a total of 3,076,604 SNPs remained for GWAS.
Using the MLM, we performed association analysis of cyanidin-3-glucosidase in 2014 and 2015 (Supplemental Fig. 1A and B) because that model was proved to be suitable for the quantitative character (Korte and Farlow, 2013). The result showed that many association signals exceeded the genome-wide significance threshold (−log10 P > 8.49) but presented a scattered distribution without any clear association peaks. This abnormal association may be related to the substantial bias in separation of the trait (Fig. 1A and C). In 2015, peak signals were found in 37.15, 8.68, 0.04, 19.89, 3.08, 10.17, 3.08, and 5.25 Mb of chromosome (Chr.) 1 to Chr. 8, respectively. And in 2014, peak signals were found in 36.51, 4.94, 3.28, 15.54, 2.01, 19.84, 4.93, and 4.12 Mb of Chr. 1 to 8. The results indicated that there were no year-stable association regions of cyanidin-3-glucosidase contents in peach flesh considering the linkage disequilibrium decay of peach [about 20 kb (Cao et al., 2016)]. Furthermore, we found that significant SNPs were far from the candidate genes involved in anthocyanin biosynthesis. For example, a CHS gene, Prupe.1G002900, was located in 0.3 Mb in Chr. 1. A UFGT gene, Prupe.2G324700, was located in 30.0 Mb in Chr. 2. A MYB gene, Prupe.3G163100, was located in 18.2 Mb in Chr. 3.
When anthocyanin content was considered as a qualitative character (anthocyanin absent/present), three models were used for association analysis (Fig. 2A–C). The QQ-plot result showed that the GWAS of GLM-PCA present a well-defined distribution and the model could obtain clean and obvious associations. The false-positive association signals were avoided by controlling population structure comparing with the GLM–no PCA model (Fig. 2A). However, MLMs present an excessive regulation because no continuous and obvious association signals were found to be higher than the genome-wide significance level (Fig. 2C). Therefore, the most prominent association signal (Chr. 1: 12,265,694 bp, −log10 P = 8.81) being located in the interval between 11.7 and 13.1 Mb on Chr. 1 of GLM-PCA (Fig. 2B) was selected for following analysis. To date, only 133 of 146 genes in this region have been functionally annotated, among which membrane-associated genes are significantly enriched (Fig. 3), including one gene encoding a chloride channel (CLC) protein, and 17 involved in sugar transport and galactosyltransferase activity (Table 2).
Manhattan and quantile-quantile plots of estimated −log10 P from association analysis of anthocyanin absent/present in fruit of 129 peach accessions using (A) general linear model (GLM)–no principal components analysis (PCA), (B) GLM-PCA, and (C) mixed linear model (MLM). Negative log10 P values from the genome-wide scan were plotted against single-nucleotide polymorphism position on each of the eight chromosomes. The dotted horizontal line indicates the genome-wide significance threshold (−log10 P = 8.49).
Citation: Journal of the American Society for Horticultural Science J. Amer. Soc. Hort. Sci. 144, 3; 10.21273/JASHS04622-18
Manhattan and quantile-quantile plots of estimated −log10 P from association analysis of anthocyanin absent/present in fruit of 129 peach accessions using (A) general linear model (GLM)–no principal components analysis (PCA), (B) GLM-PCA, and (C) mixed linear model (MLM). Negative log10 P values from the genome-wide scan were plotted against single-nucleotide polymorphism position on each of the eight chromosomes. The dotted horizontal line indicates the genome-wide significance threshold (−log10 P = 8.49).
Citation: Journal of the American Society for Horticultural Science J. Amer. Soc. Hort. Sci. 144, 3; 10.21273/JASHS04622-18
Manhattan and quantile-quantile plots of estimated −log10 P from association analysis of anthocyanin absent/present in fruit of 129 peach accessions using (A) general linear model (GLM)–no principal components analysis (PCA), (B) GLM-PCA, and (C) mixed linear model (MLM). Negative log10 P values from the genome-wide scan were plotted against single-nucleotide polymorphism position on each of the eight chromosomes. The dotted horizontal line indicates the genome-wide significance threshold (−log10 P = 8.49).
Citation: Journal of the American Society for Horticultural Science J. Amer. Soc. Hort. Sci. 144, 3; 10.21273/JASHS04622-18
The cellular component of gene ontology annotation of the 133 target genes and in comparison of all genes annotated in the genome (designated as background genes). The left and right y-axes present the proportion and number of genes among of different categories.
Citation: Journal of the American Society for Horticultural Science J. Amer. Soc. Hort. Sci. 144, 3; 10.21273/JASHS04622-18
The cellular component of gene ontology annotation of the 133 target genes and in comparison of all genes annotated in the genome (designated as background genes). The left and right y-axes present the proportion and number of genes among of different categories.
Citation: Journal of the American Society for Horticultural Science J. Amer. Soc. Hort. Sci. 144, 3; 10.21273/JASHS04622-18
The cellular component of gene ontology annotation of the 133 target genes and in comparison of all genes annotated in the genome (designated as background genes). The left and right y-axes present the proportion and number of genes among of different categories.
Citation: Journal of the American Society for Horticultural Science J. Amer. Soc. Hort. Sci. 144, 3; 10.21273/JASHS04622-18
Functional annotation of the 18 enriched genes during the quantitative trait loci for red pigments in peach fruit flesh.
Candidate gene identification using fruit flesh cultured with sugar.
In the present study, expression of 17 enriched genes associated with sugar identified through GWAS was also evaluated in fruit flesh incubated with different sugars. Our results showed that with an increase in the duration of the culture period, anthocyanin was induced by glucose, sucrose, and fructose, whereas treatment with sorbitol had minor effects comparable to those of the control mannitol (Fig. 4A). In fruit subjected to sugar induction for 12 h, we observed that glucose treatment resulted in the highest content of anthocyanin, followed by sucrose, whereas the levels of anthocyanin in flesh induced by fructose and sorbitol were lower than those induced by the mannitol control. In contrast, after 24 h of induction, the anthocyanin contents of fruit in all four sugar treatments were higher than those induced by mannitol, with the contents induced by glucose and sucrose being slightly higher than those induced by fructose.
(A) Anthocyanin content and (B) gene expression profile using RNA-seq in the fruit flesh of a red-fleshed peach ‘Tianjin Shui Mi’ induced by different sugar, including glucose, sucrose, fructose, and sorbitol, at 0, 12, and 24 h, compared with the control (mannitol treatment). The anthocyanin content is expressed as the mean ± sd of triplicates in each sample. Asterisks indicate significant differences between the sugar and the control in 12- or 24-h treatment (** P < 0.01, one-way analysis of variance). FW = fresh weight.
Citation: Journal of the American Society for Horticultural Science J. Amer. Soc. Hort. Sci. 144, 3; 10.21273/JASHS04622-18
(A) Anthocyanin content and (B) gene expression profile using RNA-seq in the fruit flesh of a red-fleshed peach ‘Tianjin Shui Mi’ induced by different sugar, including glucose, sucrose, fructose, and sorbitol, at 0, 12, and 24 h, compared with the control (mannitol treatment). The anthocyanin content is expressed as the mean ± sd of triplicates in each sample. Asterisks indicate significant differences between the sugar and the control in 12- or 24-h treatment (** P < 0.01, one-way analysis of variance). FW = fresh weight.
Citation: Journal of the American Society for Horticultural Science J. Amer. Soc. Hort. Sci. 144, 3; 10.21273/JASHS04622-18
(A) Anthocyanin content and (B) gene expression profile using RNA-seq in the fruit flesh of a red-fleshed peach ‘Tianjin Shui Mi’ induced by different sugar, including glucose, sucrose, fructose, and sorbitol, at 0, 12, and 24 h, compared with the control (mannitol treatment). The anthocyanin content is expressed as the mean ± sd of triplicates in each sample. Asterisks indicate significant differences between the sugar and the control in 12- or 24-h treatment (** P < 0.01, one-way analysis of variance). FW = fresh weight.
Citation: Journal of the American Society for Horticultural Science J. Amer. Soc. Hort. Sci. 144, 3; 10.21273/JASHS04622-18
On conducting RNA-seq analysis to assess the expression of the aforementioned 17 genes (Fig. 4B), we found that 13 showed no detectable expression. Among the remaining four genes, three (Prupe.1G56300, Prupe.1G56900, and Prupe.1G15700, corresponding to ppa004132m, ppa004439m, ppa023527m, respectively, annotated in reference genome v1.0) showed an expression pattern consistent with anthocyanin induced by sugar, although the expression levels were higher at 12 h than at 24 h. The expression level of the fourth of these genes (Prupe.1G166200) decreased with increasing culture time. Of the three genes with increased expression, Prupe.1G156300 had higher expression than Prupe.1G156900 and Prupe.1G157000.
Candidate gene identification using fruit flesh during fruit developments.
We further analyzed the expression of Prupe.1G56300, Prupe.1G56900, and Prupe.1G15700 in fruit flesh during different periods of fruit development (Fig. 5), and accordingly observed the steady expression of Prupe.1G156300 during the course of fruit development in the white-fleshed peach and induction at the mature stage in the red-fleshed peach, a pattern similar to the accumulation of anthocyanin. Prupe.1G157000 showed higher expression in the white-fleshed peach at the mature stage, in contrast to the observed anthocyanin levels. We were unable to detect the expression of Prupe.1G156900 in any of the two examined peach cultivars.
The relative expression of different genes using quantitative real-time polymerase chain reaction and anthocyanin content in the fruit flesh during the development period of white-flesh [(A) ‘Hakuho’] and red flesh [(B) ‘Tianjin Shui Mi’] peach fruit. FW = fresh weight.
Citation: Journal of the American Society for Horticultural Science J. Amer. Soc. Hort. Sci. 144, 3; 10.21273/JASHS04622-18
The relative expression of different genes using quantitative real-time polymerase chain reaction and anthocyanin content in the fruit flesh during the development period of white-flesh [(A) ‘Hakuho’] and red flesh [(B) ‘Tianjin Shui Mi’] peach fruit. FW = fresh weight.
Citation: Journal of the American Society for Horticultural Science J. Amer. Soc. Hort. Sci. 144, 3; 10.21273/JASHS04622-18
The relative expression of different genes using quantitative real-time polymerase chain reaction and anthocyanin content in the fruit flesh during the development period of white-flesh [(A) ‘Hakuho’] and red flesh [(B) ‘Tianjin Shui Mi’] peach fruit. FW = fresh weight.
Citation: Journal of the American Society for Horticultural Science J. Amer. Soc. Hort. Sci. 144, 3; 10.21273/JASHS04622-18
Discussion
GWAS is increasingly being applied in biological studies to facilitate direct correlation between phenotypic traits and the associated genetic mechanisms. The key genes for the red flesh phenotype of peach have previously been identified as PpMYB10.1 at 12.87 Mb on Chr. 3 and PpBL at 4.2 to 4.5 Mb on Chr. 4 (Zhou et al., 2015). A DBF gene, known to control flesh color, has been located at the top of linkage group 5 (0.59–0.61 Mb) in a hybrid population of the blood peach cultivar Wu Yue Xian (Shen et al., 2013). Furthermore, DBF2, which has been determined to be responsible for red flesh color in almond (Prunus dulcis), was found to map to the end of linkage group 1 (corresponding to 35.2 Mb in Chr. 1) in a cross between the almond cultivar Texas and the peach cultivar Earlygold (Donoso et al., 2016). During the study of our laboratory, 66 genes were identified through RNA-seq using different development of fruit of ‘Tianjin Shui Mi’ peach. Among of them, 13 genes were located at Chr. 1 and only ppa011068m (corresponding to 10.3 Mb in Chr. 1). In the present study, we conducted a GWAS to identify the marker associated with anthocyanin content using resequencing data. We found an obvious association signal with the GLM-PCA model and the association region to be located between 11.7 and 13.1 Mb on Chr. 1 (Fig. 2C). This locus is close to that located in an interspecific cross (Prunus davidiana clone P1908 and P. persica cv. Summergrand) (Quilot et al., 2004), which is linked to the marker CFF14 (corresponding to 9.16 Mb in Chr. 1) and gene ppa011068m (Cao et al., 2018). The different location from that described previously for the DBF2 locus may be related to the different backgrounds.
Among the genes previously annotated in the putative association region, one gene encodes a CLC protein, and a further 17 are involved in sugar transport and galactosyltransferase activity. In arabidopsis (Wei et al., 2013) and rice (Diedhiou and Golldack, 2006), CLCs have been reported to be involved in plant adaptation to salt stress by regulating chloride ion homeostasis. However, sugars not only serve as energy sources and structural materials, but also help osmosis, which has an essential role in plant growth (Archetti et al., 2009; Dong et al., 2013). In addition, sugars also can function as signal molecules in different biological pathways in different plants species (Gazzarrini and Mccort, 2001; Solfanelli et al., 2006), and notably can enhance anthocyanin production in plants (Ai et al., 2016). Sucrose is involved in the expression of numerous genes related to anthocyanin biosynthesis, as well as in the regulation of transcription factors (Cheng and Li, 2010), and can specifically induce the anthocyanin biosynthetic pathway in arabidopsis (Solfanelli et al., 2006). Similarly, exogenous glucose treatment has also been found to enhance anthocyanin content in the petals of Paeonia suffruticosa ‘Luoyang Hong’ cut flowers (Zhang et al., 2015). Moreover, these observations have been validated in Vitis vinifera cells (Gollop et al., 2001, 2002). Certain genes associated with sugar have been found to be enriched in the markers associated with anthocyanin content in peach (Nikkhah et al., 2007). Therefore, in the present study, we examined the effects of exogenous sugar treatment on fruit flesh to screen the 17 candidate genes. Our RNA-seq results indicated that among the 17 genes induced in fruit flesh; only three genes (Prupe.1G56300, Prupe.1G56900, and Prupe.1G15700) showed an expression pattern similar to that of sugar-induced anthocyanin levels. When we further analyzed the expression of these three genes in fruit flesh during different periods of fruit development, we observed that expression of Prupe.1G156300, a sugar transporter gene, was positively correlated with anthocyanin accumulation in red-fleshed fruit; however, further analysis, including functional studies, are necessary to confirm the role of this candidate gene.
It was noticed that both mannitol and sorbitol increased anthocyanin content of cultured flesh (Fig. 4A), and these findings may be interpreted as the osmotic effects of these sugars on anthocyanin biosynthesis (Do and Cormier, 1990; Zhang et al., 2015).
Conclusion
To identify the candidate gene regulating anthocyanin content in peach, we performed a GWAS and candidate gene screening, and initially detected an association signal in the 11.7 to 13.1 Mb region of Chr. 1. GO annotation of the 146 genes mapping to this region, indicated that 17 may be involved in sugar metabolism, and we accordingly focused on these in our subsequent analyses. Among these 17 genes, the expression of Prupe.1G156300, which encodes a sugar transporter, was found to be positively correlated with anthocyanin accumulation in fruit flesh of two red peach cultivars. These findings enabled us to provisionally characterize the genetic basis of anthocyanin biosynthesis in peach fruit.
Literature Cited
Ai, T.N., Naing, A.H., Arun, M., Lim, S.H. & Kim, C.K. 2016 Sucrose-induced anthocyanin accumulation in vegetative tissue of petunia plants requires anthocyanin regulatory transcription factors Plant Sci. 252 144 150
Akane, Y., Toshiko, T., Tomohiro, O., Naoki, N., Maiko, K., Kasumi, M., Toshifumi, F., Hayato, M. & Yoji, K. 2018 Single oral administration of anthocyanin rescues smoking-induced endothelial dysfunction in young smokers but sacilitates oxidative stress in non-smokers Food Nutr. Sci. 9 179 190
Allan, A.C., Hellens, R.P. & Laing, W.A. 2008 MYB transcription factors that colour our fruit Trends Plant Sci. 13 99 102
Archetti, M., Ring, T.F., Hagen, S.B., Hughes, N.M., Leather, S.R., Lee, D.W., Yadun, S.L., Ougham, H.J., Schaberg, P.G. & Thomas, H. 2009 Unravelling the evolution of autumn colours: An interdisciplinary approach Trends Ecol. Evol. 24 166 173
Beruter, J. & Studer Feusi, M.E. 1995 Comparison of sorbitol transport in excised tissue discs and cortex tissue of intact apple fruit J. Plant Physiol. 146 95 102
GitHub, Inc. 2016 BGI-FlexLab. 1 Sept. 2016. <https://github.com/BGI-flexlab/SOAPnuke/>
Bradbury, P.J., Zhang, Z., Kroon, D.E., Casstevens, T.M., Ramdoss, Y. & Buckler, E.S. 2007 TASSEL: Software for association mapping of complex traits in diverse samples Bioinformatics 23 2633 2635
Cao, K., Wang, L.R., Zhu, G.R., Fang, W.C., Chen, C.W. & Luo, J. 2012 Genetic diversity, linkage disequilibrium, and association mapping analyses of peach (Prunus persica) landraces in China Tree Genet. Genomes 8 975 990
Cao, K., Zhou, Z., Wang, Q., Guo, J., Zhao, P., Zhu, G.R., Fang, W.C., Wang, X.W., Wang, X.L., Tian, Z.X. & Wang, L.R. 2016 Genome wide association study of 12 agronomic traits in peach Nat. Commun. 7 13246
Cao, K., Ding, T.Y., Mao, D.M., Zhu, G.R., Fang, W.C., Chen, C.W., Wang, X.W. & Wang, L.R. 2018 Transcriptome analysis reveals novel genes involved in anthocyanin biosynthesis in the flesh of peach Plant Physiol. Biochem. 123 94 102
Chalker, S.L. 2002 Do anthocyanins function as osmoregulators in leaf tissues Adv. Bot. Res. 37 103 106
Chalker, S.L. 2010 Environmental significance of anthocyanins in plant stress responses Photochem. Photobiol. 70 1 9
Chen, P.N., Chu, S.C., Chiou, H.L., Kuo, W.H., Chiang, C.L. & Hsieh, Y.S. 2006 Mulberry anthocyanins, cyaniding 3-rutinoside and cyaniding 3-glucoside, exhibited an inhibitory effect on the migration and invasion of a human lung cancer cell line Cancer Lett. 235 248 259
Cheng, H.Y. & Li, D.H. 2010 Studies on the synthesis and accumulation of anthocyanin in plants with light, sugar and hormones Subtrop. Plant Sci. 39 82 86
Choi, S.W., Chang, E.J. & Ha, T.Y. 1997 Antioxidative activity of acylate anthocyani isolated from fruit and vegetables J. Food Sci. Nutr. 2 191 196
Conesa, A. & Gotz, S. 2008 Blast2GO: A comprehensive suite for functional analysis in plant genomics Intl. J. Plant Genomics 2008 1 12
Diedhiou, C.J. & Golldack, D. 2006 Salt-dependent regulation of chloride channel transcripts in rice Plant Sci. 170 793 800
Ding, T.Y. 2017 The evaluation of polyphenol in peach and its QTL mapping. Chinese Acad. Agr. Sci., Beijing, MS Thesis
Dirlewanger, E., Graziano, E., Joobeur, T., Garriga-Caldere, F., Cosson, P., Howad, W. & Arus, P. 2004 Comparative mapping and marker-assisted selection in Rosaceae fruit crops Proc. Natl. Acad. Sci. USA 101 9891 9896
Do, C.B. & Cormier, F. 1990 Accumulation of anthocyanins enhanced by a high osmotic potential in grape (Vitis vinifera L.) cell suspensions Plant Cell Rpt. 9 143 146
Dong, H.S., Myoung, G.C., Hyun, K.L., Misuk, C., Sang, B.C., Giltsu, C. & Youn, I.P. 2013 Calcium dependent sucrose uptake links sugar signaling to anthocyanin biosynthesis in Arabidopsis Biochem. Biophys. Res. Commun. 430 634 639
Donoso, J.M., Picañol, R., Serra, O., Howad, W., Alegre, S., Arús, P. & Eduardo, I. 2016 Exploring almond genetic variability useful for peach improvement: Mapping major genes and QTLs in two interspecific almond×peach populations Mol. Breed. 36 16
Eduardo, I., Pacheco, I., Chietera, G., Bassi, D., Pozzi, C., Vecchietti, A. & Rossini, L. 2011 QTL analysis of fruit quality traits in two peach intraspecific populations and importance of maturity date pleiotropic effect Tree Genet. Genomes 7 323 335
Forkmann, G. & Martens, S. 2001 Metabolic engineering and applications of flavonoids Curr. Opin. Biotechnol. 12 155 160
Frett, T.J., Reighard, G.L., Okie, W.R. & Gasic, K. 2014 Mapping quantitative trait loci associated with blush in peach [Prunus persica (L.) Batsch] Tree Genet. Genomes 10 367 381
Gazzarrini, S. & Mccourt, P. 2001 Genetic interactions between ABA, ethylene and sugar signaling pathways Curr. Opin. Plant Biol. 4 387 391
Gollop, R., Even, S., Colova, T.V. & Perl, A. 2002 Expression of the grape dihydroflavonol reductase gene and analysis of its promoter region J. Expt. Bot. 53 1397 1409
Gollop, R., Farhi, S. & Perl, A. 2001 Regulation of the leucoanthocyanidin dioxygenase gene expression in Vitis vinifera Plant Sci. 161 579 588
Gould, K., Davies, K. & Winefield, C. 2009 Anthocyanins: Biosynthesis, functions, and applications. Springer-Verlag, Heidelberg, Germany
Gyawali, S., Otte, M.L., Chao, S., Abderazzek, J., Jacob, D.L., Amezrou, R. & Verma, R.S. 2017 Genome wide association studies (GWAS) of element contents in grain with a special focus on zinc and iron in a world collection of barley (Hordeum vulgare) J. Cereal Sci. 77 266 274
Jaakola, L. 2013 New insights into the regulation of anthocyanin biosynthesis in fruits Trends Plant Sci. 18 477 483
Jia, H.H. 2013 Roles and mechanisms of sucrose and jasmonic acid signals in the regulation of strawberry fruit development. China Agr. Sci. Univ., Beijing, PhD Diss
Jiao, Y., Ma, R., Shen, Z., Yan, J. & Yu, M. 2014 Gene regulation of anthocyanin biosynthesis in two blood-flesh peach [Prunus persica (L.) Batsch] cultivars during fruit development J. Zhejiang Univ. Sci. B 15 809 819
Karageorgou, P. & Manetas, Y. 2006 The importance of being red when young: Anthocyanins and the protection of young leaves of Quercus coccifera from insect herbivory and excess light Tree Physiol. 26 613 621
Kim, T.S., He, Q., Kim, K.W., Yoon, M.Y., Ra, W.H., Li, F.P., Tong, W., Yu, J., Oo, W.H., Choi, B., Heo, E.B., Yun, B.K., Kwon, S.J., Kwon, S.W., Cho, Y.H., Lee, C.Y., Park, B.S. & Park, Y.J. 2016 Genome-wide resequencing of krice-core reveals their potential for future breeding, as well as functional and evolutionary studies in the post-genomic era BMC Genomics 17 408
Korte, A. & Farlow, A. 2013 The advantages and limitations of trait analysis with GWAS: A review Plant Methods 9 29
Lila, M.A., Burtonfreeman, B., Grace, M. & Kalt, W. 2016 Unraveling anthocyanin bioavailability for human health Annu. Rev. Food Sci. Technol. 7 375 393
Lin-Wang, K., Bolitho, K., Grafton, K., Kortstee, A., Karunairetnam, S., McGhie, T.K., Espley, R.V., Hellens, R.P. & Allan, A.C. 2010 An R2R3 MYB transcription factor associated with regulation of the anthocyanin biosynthetic pathway in Rosaceae BMC Plant Biol. 10 50
Livak, K.J. & Schmittgen, T.D. 2001 Analysis of relative gene expression data using real-time quantitative PCR and the 2−△△CT method Methods 25 402 408
Nikkhah, E., Khayamy, M., Heidari, R. & Jamee, R. 2007 Effect of sugar treatment on stability of anthocyanin pigments in berries J. Biol. Sci. 7 1412 1417
Petroni, K. & Tonelli, C. 2011 Recent advances on the regulation of anthocyanin synthesis in reproductive organs Plant Sci. 181 219 229
Quilot, B., Wu, B.H., Kervella, J., Génard, M., Foulongne, M. & Moreau, K. 2004 QTL analysis of quality traits in an advanced backcross between Prunus persica cultivars and the wild relative species P. davidiana Theor. Appl. Genet. 109 884 897
Rahim, M.A., Busatto, N. & Trainotti, L. 2014 Regulation of anthocyanin biosynthesis in peach fruits Planta 240 913 929
Revilla, P., Rodríguez, V.M., Ordás, A., Rincent, R., Charcosset, A., Giauffret, C., Melchinger, A.E., Chön, C.X., Bauer, E., Altmann, T., Brunel, D., González, J.M., Campo, L., Ouzunova, M., Álvarez, A., Galarreta, J.P., Laborde, J. & Malvar, R.N. 2016 Association mapping for cold tolerance in two large maize inbred panels BMC Plant Biol. 16 127
Shen, Z., Confolent, C., Lambert, P., Poessel, J.L., Quilot, T.B., Yu, M. & Ma, and Pascal T R. 2013 Characterization and genetic mapping of a new blood-flesh trait controlled by the single dominant locus DBF in peach Tree Genet. Genomes 9 1435 1446
Shulaev, V., Korban, S.S., Sosinski, B., Abbott, A.G., Aldwinckle, H.S., Folta, K.M., Iezzoni, A., Main, D., Arús, P., Dandekar, A.M., Lewers, K., Brown, S.K., Davis, T.M., Gardiner, S.E., Potter, D. & Veilleux, R.E. 2008 Multiple models for Rosaceae genomics Amer. Soc. Plant Biol. 147 985 1003
Solfanelli, C., Poggi, A., Loreti, E., Alpi, A. & Perata, P. 2006 Sucrose-specific induction of the anthocyanin biosynthetic pathway in Arabidopsis Plant Physiol. 140 637–646
Togninalli, M., Seren, Ü., Meng, D., Fitz, J., Nordborg, M., Weigel, D., Borgwardt, K., Korte, A. & Grimm, G.D. 2018 The AraGWAS Catalog: A curated and standardized Arabidopsis thaliana GWAS catalog Nucleic Acids Res. 46 D1150 D1156
Tomas-Barberan, F.A., Gil, M.I., Cremin, P., Waterhouse, A.L., Hess-Pierce, B. & Kader, A.A. 2001 HPLC-DAD-ESIMS analysis of phenolic compounds in nectarines, peaches, and plums J. Agr. Food Chem. 49 4748 4760
Trapnell, C., Williams, B.A., Pertea, G., Mortazavi, A., Kwan, G., van Baren, M.J., Salzberg, S.L., Wold, B.J. & Pachter, L. 2010 Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation Nat. Biotechnol. 28 511 515
Tsukaya, H. 2004 Leaf shape: Genetic controls and environmental factors Intl. J. Dev. Biol. 49 547 555
Tuan, P.A., Bai, S., Yaegaki, H., Tamura, T. & Oda, K. 2015 The crucial role of PpMYB10.1 in anthocyanin accumulation in peach and relationships between its allelic type and skin color phenotype BMC Plant Biol. 15 280
Turner, S.D. 2014 qqman: An R package for visualizing GWAS results using Q-Q and manhattan plots. 30 Nov. 2017. <http://cran.r-project.org/web/packages/qqman/>
Turuspekov, Y., Baibulatova, A., Yermekbayev, K., Tokhetova, L., Chudinov, V., Sereda, G., Ganal, M., Griffiths, S. & Abugalieva, S. 2017 GWAS for plant growth stages and yield components in spring wheat (Triticum aestivum L.) harvested in three regions of Kazakhstan BMC Plant Biol. 17 190
Verde, I., Abbott, A.G., Scalabrin, S., Jung, S., Shu, S., Marroni, F., Zhebentyayeva, T., Dettori, M.T., Grimwood, J., Cattonaro, F., Zuccolo, A., Rossini, L., Jenkins, J., Vendramin, E., Meisel, L.A., Decroocq, V., Sosinski, B., Prochnik, S., Mitros, T., Policriti, A., Cipriani, G., Dondini, L., Ficklin, S., Goodstein, D.M., Xuan, P., Del Fabbro, C., Aramini, V., Copetti, D., Gonzalez, S., Horner, D.S., Falchi, R., Lucas, S., Mica, E., Maldonado, J., Lazzari, B., Bielenberg, D., Pirona, R., Miculan, M., Barakat, A., Testolin, R., Stella, A., Tartarini, S., Tonutti, P., Arús, P., Orellana, A., Wells, C., Main, D., Vizzotto, G., Silva, H., Salamini, F., Schmutz, J., Morgante, M. & Rokhsar, D.S. 2013 The high-quality draft genome of peach (Prunus persica) identifies unique patterns of genetic diversity, domestication and genome evolution Nat. Genet. 45 487 494
Verde, I., Jenkins, J., Dondini, L., Micali, S., Pagliarani, G., Vendramin, E., Paris, R., Aramini, V., Gazza, L., Rossini, L., Bassi, D., Troggio, M., Shu, S.Q., Grimwood, J., Tartarini, S., Dettori, M.T. & Schmutz, J. 2017 The peach v2.0 release: High-resolution linkage mapping and deep resequencing improve chromosome-scale assembly and contiguity BMC Genomics 18 225
Wang, L.R. & Zhu, G.R. 2005 Descripters and data standard for peach. China Agr. Press, Beijing, China
Wei, Q., Liu, Y., Zhou, G., Li, Q., Yang, C. & Peng, S. 2013 Overexpression of CsCLCc, a chloride channel gene from Poncirus trifoliata, enhances salt tolerance in Arabidopsis Plant Mol. Biol. Rpt. 31 1548 1557
Wen, L.N., Jiang, X.W., Sun, J.X., Li, X., Li, X.S., Tian, L.M., Li, Y. & Bai, W.B. 2018 Cyanidin-3-O-glucoside promotes the biosynthesis of progesterone through the protection of mitochondrial function in Pb-exposed rat leydig cells Food Chem. Toxicol. 112 427 434
Xia, E.Q., Deng, G.F., Guo, Y.J. & Li, H.B. 2010 Biological activities of polyphenols from grapes Intl. J. Mol. Sci. 11 622 646
Xu, W., Dubos, C. & Lepiniec, L. 2015 Transcriptional control of flavonoid biosynthesis by MYB-bHLH-WDR complexes Trends Plant Sci. 20 176 185
Yang, J., Lee, S.H., Goddard, M.E. & Visscher, P.M. 2011 GCTA: A tool for genome-wide complex trait analysis Amer. J. Hum. Genet. 88 76 82
Yang, S.W., Tian, P., Li, L.J., Lu, D.T., Qiao, L., Zhao, J.J., Qiao, L., Chuan, G., Zheng, J. & Zhang, J.C. 2018 Extraction of anthocyanins from purple wheat and its effect on antioxidant activity and inhibitory on tumor cells J. Agr. Sci. Technol. 20 1 8
Ye, J., Fang, L., Zheng, H.K., Zhang, Y., Chen, J., Zhang, Z.J., Wang, J., Li, S.T., Li, R.Q., Bolund, L. & Wang, J. 2006 WEGO: A web tool for plotting GO annotations Nucleic Acids Res. 34 293 297
Zhang, C., Fu, J., Wang, Y., Gao, S., Du, D., Wu, F., Guo, J. & Dong, L.B. 2015 Glucose supply improves petal coloration and anthocyanin biosynthesis in Paeonia suffruticosa ‘Luoyang Hong’ cut flowers Postharvest Biol. Technol. 101 73 81
Zhang, G.H. 2008 Theories on the cultivation of fruit trees. China Agr. Press, Beijing, China
Zhou, H., Lin-Wang, K., Wang, H., Gu, C., Dare, A.P., Espley, R.V., He, H., Allan, A.C. & Han, Y. 2015 Molecular genetics of blood-fleshed peach reveals activation of anthocyanin biosynthesis by NAC transcription factors Plant J. 82 105 121
Zhou, L.J., Li, Y.Y., Zhang, R.F., Zhang, C.L., Xie, X.B., Zhao, C. & Hao, J.Y. 2017 The sumo E3 ligase mdsiz1 promotes anthocyanin accumulation by sumoylating MdMYB1 under low temperature conditions in apple Plant Cell Environ. 40 2068 2080
Zhu, H., Xia, R., Zhao, B., An, Y.Q., Dardick, C.D., Callahan, A.M. & Liu, Z.R. 2012 Unique expression, processing regulation, and regulatory network of peach (Prunus persica) miRNAs BMC Plant Biol. 12 149
Manhattan and quantile-quantile plots of estimated ·log10 P from association analysis of cyanidin-3-glucoside content in 2014 (A) and 2015 (B) in fruit of 129 accessions using mixed linear model. Negative log10 P values from the genome-wide scan were plotted against single-nucleotide polymorphism position on each of the eight chromosomes. The dotted line indicates the genome-wide significance threshold (·log10 P = 8.49).
Citation: Journal of the American Society for Horticultural Science J. Amer. Soc. Hort. Sci. 144, 3; 10.21273/JASHS04622-18
Manhattan and quantile-quantile plots of estimated ·log10 P from association analysis of cyanidin-3-glucoside content in 2014 (A) and 2015 (B) in fruit of 129 accessions using mixed linear model. Negative log10 P values from the genome-wide scan were plotted against single-nucleotide polymorphism position on each of the eight chromosomes. The dotted line indicates the genome-wide significance threshold (·log10 P = 8.49).
Citation: Journal of the American Society for Horticultural Science J. Amer. Soc. Hort. Sci. 144, 3; 10.21273/JASHS04622-18
Manhattan and quantile-quantile plots of estimated ·log10 P from association analysis of cyanidin-3-glucoside content in 2014 (A) and 2015 (B) in fruit of 129 accessions using mixed linear model. Negative log10 P values from the genome-wide scan were plotted against single-nucleotide polymorphism position on each of the eight chromosomes. The dotted line indicates the genome-wide significance threshold (·log10 P = 8.49).
Citation: Journal of the American Society for Horticultural Science J. Amer. Soc. Hort. Sci. 144, 3; 10.21273/JASHS04622-18
Prunus samples used in this study and their key agronomic traits.
