Sean Myles’s research while affiliated with Dalhousie University and other places

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Publications (156)


Heterozygosity and ploidy for accessions from Canada's Apple Biodiversity Collection. (a) Histogram of heterozygosity by individual for all accessions genotyped (n = 970). A blue vertical line indicates the mean value of the diploids (2×), as determined using data from the USDA NPGS Apple Collection. The orange vertical line indicates the mean heterozygosity value for triploids (3×) based on data from the USDA. The grey vertical line indicates the inferred ploidy threshold used as a cut-off between the two ploidy levels. (b) Boxplots showing heterozygosity by individual for known diploids (blue, n = 139) and triploids (orange, n = 48) with the horizontal grey line indicating the inferred ploidy threshold between the two ploidy levels.
Genetic similarity among diploid and triploid accessions as determined using genomic data. (a) Principal components analysis (PCA) performed using 51,823 single nucleotide polymorphisms (SNPs). Principal component 1 (PC1) and principal component 2 (PC2) are shown with the percentage of variance explained by each PC indicated in parentheses. Each dot indicates an accession and is labeled by the inferred ploidy level, either diploid (blue) or triploid (orange). (b) Density plots showing IBS (identity-by-state) values for each pairwise comparison. IBS values were calculated based on the average proportion of alleles shared at the genotyped SNPs (105,524 SNPs). The blue curve represents all pairwise comparisons between diploids to other diploids, the gray curve represents all comparisons between diploids and triploids, and the orange curve represents all comparisons between triploids to other triploids.
Boxplots showing phenotype values for inferred diploids (blue) and triploids (orange) for the 10 traits evaluated. The number of accessions in each group is reported beside the ploidy level in all the graphs on the x-axis. A Mann-Whitney U-test was performed to compare trait values between diploids and triploids, and the resulting p-values were Bonferroni-corrected for multiple testing. The test results are shown only for the trait where there was a significant difference between ploidy levels after multiple testing corrections. The following traits are shown: (a) acidity, (b) soluble solid content (SSC), (c) SSC divided by acidity, (d) weight, (e) firmness, (f) change in firmness, (g) phenolic content, (h) flowering date, (i) harvest date, and (j) time to ripen.
An overlapping density plot showing the date of release (when known) for diploid and triploid apple accessions. The density distribution for diploids (n = 299) is shown in blue and triploids (n = 32) are shown in orange. A Mann-Whitney U-test was performed to compare release year across groups (W = 5,800, p = 0.048).
Comparing diploid and triploid apples from a diverse collection
  • Article
  • Full-text available

February 2025

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16 Reads

Fruit Research

Elaina Greaves

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Thomas Davies

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Sean Myles

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Apples (Malus X. domestica Borkh.) are an economically important fruit species and are primarily diploid, although other ploidy levels exist. The impact of ploidy on agricultural traits in apple is not well understood but is an important factor to consider for breeding and production of apples. We used heterozygosity to infer ploidy for 970 apple accessions from a diverse collection. Next, we contrasted inferred diploid and inferred triploid apples across 10 agriculturally important traits. After correction for multiple testing, we determined that triploids have significantly higher phenolic content, but do not significantly differ from diploids for any other trait. We also determined that triploid varieties have significantly earlier release dates than diploids, suggesting that contemporary breeding programs primarily release diploid varieties. Ultimately, our results provide evidence that phenotypic differences between trees of differing ploidy are subtle and often insignificant and that there are limited measurable benefits to the use of triploids for apple production.

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Figure 1. Methodology of landmarking. (a) Original colour corrected images that were used to 118 extract the contour of the apple. (b) Following binary conversion, two landmarks were placed in the 119 center of the top and the bottom of the fruit to provide reference points to align the fruit to each 120 other in analysis. (c) 50 pseudo-landmarks were placed on each half of the fruit with one removed 121 at the top for a total of 99 pseudo-landmarks. 122 123 Following the calculation of 99 pseudo-landmarks for each image, additional linear 124 measurements were calculated based on the rotated and scaled images. Using the oriented fruit, 125 width was calculated as the di^erence between the minimum and maximum of the x coordinate 126 values, while length was calculated as the same di^erence for the y coordinates. Aspect ratio was 127 calculated by dividing the width measurement by the length. The shoelace algorithm, which 128 calculates the area of a polygon, was used to calculate the area of each apple fruit in cm 2 . 129 Solidity was calculated by dividing the area of each fruit by the convex hull area. The convex 130 hull area was calculated separately and represents a contour that fully contains all landmarks. 131 Thus, higher solidities indicate that there was less empty area between the convex hull and the 132 contour of the fruit, while lower solidity values indicate a less circular fruit with more pronounced 133 gaps between the convex hull and contour. Linear measurements were averaged across within-tree 134 replicates then adjusted based on position in the orchard using a restricted maximum likelihood 135 (REML) model, as described by Watts et al. (2021) using the R packages lme4 (Bates et al., 2024), 136 pbkrtest (Halekoh & Højsgaard, 2024), lsmeans (Lenth, 2018), and lattice (Sarkar, 2008). This 137 process reduced the dataset from 743, the number of individual trees sampled, to 534, the number 138 of genetically unique accessions sampled. 139
Figure 2. Correlations of measurements from 534 apple accessions for length, width, area, and 178 harvest weight. Spearman's rank correlation coe^icient (ρ) and Bonferroni-correct (based on the 179 total 45 comparisons) associated p-value are reported for each correlation. 180
Figure 3. Morphospace of theoretical apples generated using inverse PCA with values for the 200 measured 534 apple accessions indicated along PC1 and PC3. The amount of variation explained 201 by each PC is reported in parentheses and accessions are coloured based on their aspect ratio. 202
Figure 4. Correlations between PC1, calculated using a pseudo-landmark approach, and (a) aspect 210 ratio, (b) area, and (c) harvest weight across 534 apple accessions. Spearman rank correlation 211 coe^icients (ρ) and p-values are reported for each correlation. 212
Differences in apple fruit shape are independent of fruit size

January 2025

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131 Reads

Kylie DeViller

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Sean Myles

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[...]

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Premise Fruit quality is crucial in breeding new apple accessions. Before tasting, consumers assess freshness and flavour based on the physical appearance of fruit. Understanding how fruit quality traits such as shape and size vary across diverse apples provides a foundation for future breeding efforts. Methods We analyzed images of 5724 apples representing 743 different trees and 534 unique accessions from Canada’s Apple Biodiversity Collection to quantify variation in fruit shape and size. To achieve this, we used a pseudo-landmarking approach paired with traditional linear measurements including length, width, area, solidity, and aspect ratio. We also incorporated previously collected fruit weight measurements from the same trees. Results Using a comprehensive measure of shape, we determined that the primary source of variation in apple fruit shape was the width to length (aspect) ratio of the fruit. This variation was not significantly correlated with differences in fruit size from its area and harvest weight. Conclusions Our findings indicate that two critical aspects of morphological variation in apple—fruit shape and size—are independent, suggesting it is possible to select for a diverse range of fruit shapes while maintaining a consistent and marketable size.


Figure 1. Heterozygosity and ploidy for varieties from Canada's Apple
Figure 2. Relatedness among diploid and triploid varieties as determined using
Figure 3. Boxplots showing phenotype values for diploids (blue) and triploids
Figure 4. An overlapping density plot showing the date of release (when
Comparing diploid and triploid apples from a diverse collection

July 2024

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99 Reads

Apples (Malus X. domestica Borkh.) are an economically important fruit species and the focus of continuing breeding efforts around the world. While most apple varieties are diploid, ploidy levels vary across the species, and triploids may be used in breeding despite poor fertility. The impact of ploidy on agricultural traits in apple is not well understood but is an important factor to consider when breeding new apple varieties. Here, we use mean heterozygosity values to categorize 970 apple accessions as diploid or triploid and then contrast apples of varying ploidy levels across 10 agriculturally important traits with sample sizes ranging from 427 to 928 accessions. After correction for multiple testing, we determine that triploids have significantly higher phenolic content. By examining historical release dates for apple varieties, our findings suggest that contemporary breeding programs are primarily releasing diploid varieties, and triploids tend to be older varieties. Ultimately, our results suggest that phenotypic differences between diploids and triploids are subtle and often insignificant indicating that triploids may not provide substantial benefit above diploids to apple breeding programs.


Large-scale apple GWAS reveals NAC18.1 as a master regulator of ripening traits

November 2023

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80 Reads

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8 Citations

Fruit Research

Apple quality traits such as fruit texture, sugar content, and firmness retention during storage are key targets for breeders. Understanding the genetic control of fruit quality traits can enable the development of genetic markers, useful for marker-assisted breeding of new apple cultivars. We made use of over 260,000 single nucleotide polymorphisms (SNPs) genotyped across 1,054 apple accessions from Canada's Apple Biodiversity Collection to perform genome-wide association for 21 fruit quality and phenology traits. We identified two loci on chromosome 15 and 16 associated with phenolic content and a locus on chromosome 10 associated with softening. In addition, we determined that allelic variation at the NAC18.1 transcription factor was associated with numerous traits including harvest date, firmness at harvest, and firmness after storage. Our analyses suggest that NAC18.1 independently acts as a high level regulator of multiple ripening related traits and we propose a model for the allelic effects at NAC18.1 on apple ripening and softening.


VOC composition across 515 apple varieties. (a) The number of VOCs detected by VOC class. (b) The total volatile abundance by VOC class. (c) The ubiquity of each VOC (x-axis) is plotted against its abundance (y-axis). Ubiquity is defined as the number of samples in which a VOC was detected.
Apple volatilome variation is associated with harvest date. (a) PCA bi-plot of PC1 and PC2 derived from a matrix of 106 VOCs across 515 apple varieties. Each point is a unique apple variety that is coloured according to its harvest date. (b) Scatter plot of PC1 values and harvest date across 515 varieties. (c) Scatter plot of VOC ubiquity (i.e., the number of VOCs detected per sample) and harvest date across 515 varieties. (d) Scatter plot of total volatile abundance and harvest date across 515 varieties. Lines of best fit, R² and P values result from Pearson correlations between variables.
GWAS of 1-hexanol and 1-butanol across 515 apple varieties using 250,579 SNPs. (a) Manhattan plot for 1-hexanol. (b) Manhattan plot for 1-butanol. The horizontal red line represents the significance threshold after correcting for multiple comparisons (see Methods). Chromosome 'R' is composed of contigs that remain unanchored to the reference genome.
GWAS of several esters across 515 apple varieties using 250,579 SNPs. Genome-wide manhattan plots are shown for (a) butyl acetate, (b) pentyl acetate, (c) hexyl acetate, (d) isobutyl acetate, (e) n-propyl acetate, (f) 2-methylbutyl acetate, and the (g) sum of all esters. The horizontal red lines represent the significance threshold after correcting for multiple comparisons (see Methods). Chromosome 'R' is composed of contigs that remain unanchored to the reference genome. (h) A manhattan plot showing only the locus of large effect on chromosome 2. The vertical gray bars indicate the locations of annotated genes within the region and gene names appear at the top of each bar.
Genomic insights into apple aroma diversity

September 2023

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70 Reads

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5 Citations

Fruit Research

An apple's aroma is a major determinant of its desirability by consumers. To better understand the aroma of apples, 2-dimensional gas-chromatography mass-spectrometry (2D-GCMS) was used to quantify 106 volatile organic compounds (VOCs) from 515 apple varieties. We identified esters and aldehydes as the most abundant classes of VOCs, with butyl acetate and hexyl acetate being present in nearly every variety. Principal component analysis (PCA) revealed that the primary axis of variation in the apple volatilome is correlated with harvest date, with early-harvested apples expressing a greater number and higher concentration of VOCs compared to late-harvested apples. Genome-wide association studies (GWAS) using 250,579 single nucleotide polymorphisms (SNPs) identified a significant association between SNPs near the alcohol acyltransferase (AAT1) locus and the abundance of several esters. Additionally, strong associations were observed between SNPs at the NAC18.1 transcription factor locus and the abundances of 1-hexanol and 1-butanol, which serve as precursors for hexyl acetate and butyl acetate, respectively. These findings provide a foundation for understanding the genetic basis of apple aroma production and pave the way for the genomics-assisted enhancement of the aroma profiles of apple varieties to meet consumer preferences.


Phenotype distributions for ripening time, phenolic content, and softening. Green and orange bars represent accessions selected for pooled sequencing.
Manhattan plots for genome wide delta-AFe and chi-squared test p-values for ripening time. (a) Delta-AFe values and (b) chi-squared test p-values from variants detected across the genome. (c), (d) Zoom-in plots for signals on chromosome 3 and chromosome 4. Yellow bars indicate gene coding regions. Red bar outlines the NAC18.1 coding region. The red dot is the D5Y SNP, a putatively causal non-synonymous mutation previously identified in the NAC18.1 gene⁶. 'R' on the X-axis of the genome-wide plots indicates the 'random' chromosome containing contigs that remain unanchored to the reference genome.
Manhattan plots of delta-AFe and chi-squared test p-values for phenolic content. (a) Delta-AFe values and (b) chi-squared test p-values from variants detected across the genome. (c), (d) Zoom-in plots for signals on chromosome 4, chromosome 8, and 16. Yellow bars indicate protein coding regions.
Manhattan plots for genome wide delta-AFe and chi-squared test p-values for apple softening. (a) Delta-AFe values and (b) chi-squared test p-values from variants detected across the genome. (c), (d) Zoom-in plots for signals on chromosome 6 and chromosome 17. Yellow bars indicate protein coding regions.
Pool-seq of diverse apple germplasm reveals candidate loci underlying ripening time, phenolic content, and softening

May 2023

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44 Reads

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6 Citations

Fruit Research

Ripening time, softening, and phenolic content are phenotypes of considerable commercial importance in apples. Identifying causal genetic variants controlling these traits not only advances marker-assisted breeding, but it is also an essential step for the application of gene editing technologies in apples. To advance the discovery of genetic variants associated with these phenotypes, we examined allele frequency differences between groups of phenotypically extreme individuals from Canada’s Apple Biodiversity Collection using pooled whole genome sequencing (pool-seq). We sequenced pooled DNA samples to an average read depth of 150x and scanned the genome for allelic differentiation between pools. For each phenotype, we identified >20 million genetic variants and identified numerous candidate genes. We identified loci on chromosomes 3 and 4 associated with ripening time, the former suggesting that regulatory variants upstream of a previously identified transcription factor NAC18.1 may be causal. Our analysis identified candidate regions on chromosomes 4, 8, and 16 associated with phenolic content, and suggested a cluster of UDP-Glycosyltransferase family genes as candidates for polyphenol production. Further, we identified regions on chromosomes 17 and 10 associated with softening and suggest a Long-chain fatty alcohol dehydrogenase family gene as putatively causal.


Description of the 278,231 SNPs genotyped across 11,175 apple accessions. (A) The number of SNPs on each chromosome, with the final chromosome (R) representing SNPs located on unassembled contigs. (B) The inter-SNP distance between pairs of neighbouring SNPs. SNPs on the unassembled contigs were removed prior to this analysis. The mean distance between neighbouring SNPs (2,431 bp) is indicated. (C) A zoom-in of plot (B) showing the inter-SNP distance for pairs of SNPs less than 100 bp apart. (D) Minor allele frequency (MAF) distribution for all SNPs. The mean MAF (0.149) is indicated.
Genomic PCA of 1,175 apple accessions. PCA was performed using 180,075 LD-pruned SNPs. PC1 vs. PC2 is plotted, with the amount of variance explained by each PC indicated in parentheses. Accessions are labeled based on origin: Canada (gray) and USDA (blue). Accessions are primarily Malus domestica, but 98 accessions originating from the USDA are identified as Malus sieversii (orange).
Genotyping-by-sequencing of Canada’s apple biodiversity collection

August 2022

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54 Reads

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9 Citations


Phenotypic differences between commonly grown dessert apple varieties and cider apple varieties from England and France. (a) Biplot of the first and second principal components (PC1 vs. PC2) generated from 10 phenotypes. (b) The difference between dessert and cider (English and French) varieties along PC1. (c) The difference between dessert and cider (English and French) varieties along PC2. The p‐values shown above each pairwise comparison are from a Wilcoxon rank‐sum test. (d) Density plot of pairwise Euclidean distances generated from 10 phenotypes for comparisons within dessert apples and for comparisons between dessert apples and both English and French cider apples. (e) The average Euclidean distance of each of the dessert apple varieties from English cider varieties (x‐axis) and French cider varieties (y‐axis). Apple varieties with lower values along each axis are more phenotypically similar to cider apples than those with higher values.
Density plots for phenotypes of English cider apples, French cider apples and dessert apples. The x‐axis shows the phenotype names and units. The y‐axis shows the density. Phenotypes which include delta (Δ) represent the percent change in the phenotype during 3 months of cold storage.
Cider and dessert apples: What is the difference?

June 2022

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231 Reads

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6 Citations

Societal Impact Statement Apples are among the most widely consumed fruits in the world, with a third of all apples being pressed into apple juice or fermented into cider. Cider has grown in popularity in Canada and the United States, and North American cider makers are increasingly interested in using traditional European ‘cider apples’ rather than using commonly grown ‘dessert apples’ that are grown primarily for fresh consumption. While we find that commonly grown dessert apples do differ from European cider apples for a small number of cider making characteristics, our results show that dessert apples are most often indistinguishable from cider apples across 10 traits. Our work provides a first step towards quantifying the differences between these two apple types.


PCA of ten phenotypes in wild (N = 79) and cultivated apples (N = 801)
A) PC1 vs PC2. B) PC1 vs PC3. The proportion of the variance explained by each PC is shown in parentheses on each axis. C) The difference between wild and cultivated apples for PCs 1, 2 and 3 are shown as violin plots. P values from a Wilcoxon test comparing PC values between cultivated and wild apples are shown for each of the first three PCs.
Overlapping density plots of 10 phenotypes comparing values from wild and cultivated apples
The phenotype associated with each plot is shown along the X axis. The W and Bonferroni-corrected p values report the results of performing a Wilcoxon rank sum test of the difference between the phenotypic distributions of wild and cultivated apples.
Phenotype values of cultivated apples as a function of their release year with a comparison to values in their wild ancestor, M. sieversii
Phenotypes include phenolic content (A), firmness change during storage (B), flowering date (C), and soluble solids (D). Values for cultivated apples are blue, and the values observed for M. sieversii are represented in yellow as a violin plot on the left side of each plot. The R and p values from a Pearson correlation between phenotypic values and release year are shown within each scatter plot.
Sample sizes by phenotype
Phenotypic divergence between the cultivated apple (Malus domestica) and its primary wild progenitor (Malus sieversii)

March 2022

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162 Reads

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15 Citations

An understanding of the relationship between the cultivated apple (Malus domestica) and its primary wild progenitor species (M. sieversii) not only provides an understanding of how apples have been improved in the past, but may be useful for apple improvement in the future. We measured 10 phenotypes in over 1000 unique apple accessions belonging to M. domestica and M. sieversii from Canada’s Apple Biodiversity Collection. Using principal components analysis (PCA), we determined that M. domestica and M. sieversii differ significantly in phenotypic space and are nearly completely distinguishable as two separate groups. We found that M. domestica had a shorter juvenile phase than M. sieversii and that cultivated trees produced flowers and ripe fruit later than their wild progenitors. Cultivated apples were also 3.6 times heavier, 43% less acidic, and had 68% less phenolic content than wild apples. Using historical records, we found that apple breeding over the past 200 years has resulted in a trend towards apples that have higher soluble solids, are less bitter, and soften less during storage. Our results quantify the significant changes in phenotype that have taken place since apple domestication, and provide evidence that apple breeding has led to continued phenotypic divergence of the cultivated apple from its wild progenitor species.


Genomic consequences of apple improvement

December 2021

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386 Reads

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80 Citations

Horticulture Research

The apple ( Malus domestica ) is one of the world’s most commercially important perennial crops and its improvement has been the focus of human effort for thousands of years. Here, we genetically characterise over 1000 apple accessions from the United States Department of Agriculture (USDA) germplasm collection using over 30,000 single-nucleotide polymorphisms (SNPs). We confirm the close genetic relationship between modern apple cultivars and their primary progenitor species, Malus sieversii from Central Asia, and find that cider apples derive more of their ancestry from the European crabapple, Malus sylvestris , than do dessert apples. We determine that most of the USDA collection is a large complex pedigree: over half of the collection is interconnected by a series of first-degree relationships. In addition, 15% of the accessions have a first-degree relationship with one of the top 8 cultivars produced in the USA. With the exception of ‘Honeycrisp’, the top 8 cultivars are interconnected to each other via pedigree relationships. The cultivars ‘Golden Delicious’ and ‘Red Delicious’ were found to have over 60 first-degree relatives, consistent with their repeated use by apple breeders. We detected a signature of intense selection for red skin and provide evidence that breeders also selected for increased firmness. Our results suggest that Americans are eating apples largely from a single family tree and that the apple’s future improvement will benefit from increased exploitation of its tremendous natural genetic diversity.


Citations (42)


... A number of quantitative trait loci (QTL) for MD in apple were identified based on linkage mapping studies in bi-parental populations (Chagn e et al., 2014). Whereas, genome-wide association studies (GWAS) of unrelated individuals revealed a common large-effect QTL on chromosome (Chr) 3, with a NAC TF designated MdNAC18.1 being a strong candidate gene for MD (Larsen et al., 2019;Migicovsky et al., 2016;Urrestarazu et al., 2017;Watts et al., 2023). The MdNAC18.1 locus contains many DNA polymorphisms, but the causal variant(s) underlying MD remains unclear (Migicovsky et al., 2021). ...

Reference:

Autosuppression of MdNAC18.1 endowed by a 61‐bp promoter fragment duplication delays maturity date in apple
Large-scale apple GWAS reveals NAC18.1 as a master regulator of ripening traits

Fruit Research

... The aroma of the apple not only determines the degree of consumer appeal, but also reflects the physiological condition of the apple, which is fundamentally determined by complex genetics [45]. From another perspective, it also depends on the combination of various volatile compounds and the odor threshold and concentration of each volatile substance [46]. ...

Genomic insights into apple aroma diversity

Fruit Research

... A non-synonymous SNP at the fifth amino acid position in MdNAC18.1 was first reported as a candidate causal variant for maturity date (Migicovsky et al., 2016). However, recent studies suggest that mutations in the promoter region that affect the transcription of MdNAC18.1, instead of non-synonymous mutations in the protein coding region, are likely the causal variants for maturity date (Davies and Myles, 2023;Watts et al., 2023). In this study, our results indicate that a regulatory variant which arose from a 61-bp fragment duplication in the promoter of MdNAC18.1 negatively autoregulates its own expression, which is likely responsible for the delay in maturity date. ...

Pool-seq of diverse apple germplasm reveals candidate loci underlying ripening time, phenolic content, and softening

Fruit Research

... Their findings indicate that most varieties are "sweet" or "sharp" rather than "bitter" and that those that are "sharp" (high acid) and "bitter" (high phenolic content) tend to vary more in these traits across years. In comparison, Soomro et al. (2022) focus on commonly grown dessert apples in North America, contrasting them with European cider apples across 10 traits important to cider production, and find that dessert apples are often indistinguishable from cider apples. Together, these articles highlight a range of traits and methods for trait measurement, using the lens of plant breeding and production to consider what makes a desirable, and successful, fruit. ...

Cider and dessert apples: What is the difference?

... A previous study on phenotypic characteristics of apple cultivars and their wild progenitors revealed significant changes during apple breeding and substantial differences in fruit weight, acidity, and phenolic contents among apple cultivars and their wild ancestors, reflecting the positive effects of apple domestication and breeding [26]. Moradi et al. [27] examined various traits of Malus orientalis (Uglitzk.) ...

Phenotypic divergence between the cultivated apple (Malus domestica) and its primary wild progenitor (Malus sieversii)

... Genotyping approaches could act as an alternate or complementary method to support robust cultivar labelling. A great deal of C. sativa genotyping research has helped cement the use of genetic markers in screening for genes associated with sex, THCA vs. cannabidiolic acid (CBDA) production, or to classify and cluster cultivars [23][24][25][26][27][28][29][30][31][32][33]. Others have explored the use of simple sequence repeat (SSR) markers to differentiate between cultivars [34]. ...

Cannabis labelling is associated with genetic variation in terpene synthase genes

Nature Plants

... Triploid apple varieties are often cited as producing larger fruit, being more disease-resistant, and being more vigorous [9,13] . Contemporary breeding programs may intentionally incorporate triploid apple accessions [14] , however, this is rare due to fertility-associated challenges [15] . ...

Quantifying apple diversity: A phenomic characterization of Canada’s Apple Biodiversity Collection

... However, in the present study no association between high ethylene production and softer fruit was found when comparing different I AD intervals within cultivar and year. Recent studies showed that differences in genotype regarding ethylene production do not solely explain differences in fruit ripening rates and that differences in ethylene perception and downstream signaling are also important [15,66,67]. ...

Apple Ripening Is Controlled by a NAC Transcription Factor

... A topic role is played by the vigor of the rootstock/scion combination. Some authors described the interactions between the inherent vigor of the scion cultivar and that conferred by the rootstock on vine growth and yield performances concluding that rootstocks could be selected to modulate overall vine vigor, yield [14], and Ravaz index (the relative ratio of reproductive to vegetative growth). Rootstocks can also have an impact on nutrient uptake [15,16] and can confer a diferent ability to extract water from soil and transfer it to the canopy [17] or to tolerate salinity or fooding [18,19]. ...

Grapevine rootstocks affect growth‐related scion phenotypes