Data from: A quantitative genetic basis for leaf morphology in a set of precisely defined tomato introgression lines
Chitwood, Daniel H., University of California, Davis
Kumar, Ravi, University of California, Davis
Headland, Lauren R., University of California, Davis
Ranjan, Aashish, University of California, Davis
Covington, Michael F., University of California, Davis
Ichihashi, Yasunori, University of California, Davis
Fulop, Daniel, University of California, Davis
Jiménez-Gómez, José M., University of California, Davis
Peng, Jie, University of California, Davis
Maloof, Julin N., University of California, Davis
Sinha, Neelima R., University of California, Davis
Published Jul 22, 2013 on Dryad.
https://doi.org/10.5061/dryad.rm5v5
Cite this dataset
Chitwood, Daniel H. et al. (2013). Data from: A quantitative genetic basis for leaf morphology in a set of precisely defined tomato introgression lines [Dataset]. Dryad. https://doi.org/10.5061/dryad.rm5v5
Abstract
Introgression lines (ILs), in which genetic material from wild tomato species is introgressed into a domesticated background, have been used extensively in tomato (Solanum lycopersicum) improvement. Here, we genotype an IL population derived from the wild desert tomato Solanum pennellii at ultrahigh density, providing the exact gene content harbored by each line. To take advantage of this information, we determine IL phenotypes for a suite of vegetative traits, ranging from leaf complexity, shape, and size to cellular traits, such as stomatal density and epidermal cell phenotypes. Elliptical Fourier descriptors on leaflet outlines provide a global analysis of highly heritable, intricate aspects of leaf morphology. We also demonstrate constraints between leaflet size and leaf complexity, pavement cell size, and stomatal density and show independent segregation of traits previously assumed to be genetically coregulated. Meta-analysis of previously measured traits in the ILs shows an unexpected relationship between leaf morphology and fruit sugar levels, which RNA-Seq data suggest may be attributable to genetically coregulated changes in fruit morphology or the impact of leaf shape on photosynthesis. Together, our results both improve upon the utility of an important genetic resource and attest to a complex, genetic basis for differences in leaf morphology between natural populations.
Usage notes
Supplemental Figure 1: S. pennellii introgression summary for all 76 ILs.
Supplemental Figure 1: S. pennellii introgression summary for all 76 ILs. Graphical representation of introgression boundaries from Supplemental Table 2 online. Gridlines represent 10Mb intervals on each chromosome.
tpc112391_Supplemental Figure 1.pdf
Supplemental Figure 2: RNAseq-based genotyping of all chromosomes.
Supplemental Figure 2: RNAseq-based genotyping of all chromosomes. Shown are the S. pennellii introgression regions for ILs covering chromosomes 1 to 12 (A-L) as determined by RNA-Seq. The depth of coverage (distance from midpoint on y-axis) and genotype (color and direction on y-axis) of each SNP/indel is plotted against chromosomal position (x-axis). Polymorphisms that match S. pennellii are colored green and plotted on the top half of each IL panel, while polymorphisms matching cv. M82 are plotted in magenta in the bottom halves. The coloring is on a continuum such that the color approaches black as a position’s genotype approaches heterozygosity. The y-axis tick marks indicate depths of coverage ranging from 0 to 100. Subsequent to genotyping, introgression boundaries consistent between the RNA-Seq and RESCAN analyses were delineated. Using these breakpoints, S. pennellii and cv. M82 regions are summarized by horizontal lines at the top and bottom of each IL panel, respectively.
tpc112391_Supplemental Figure 2.pdf
Supplemental Figure 3: RESCAN-based genotyping of all chromosomes.
Supplemental Figure 3: RESCAN-based genotyping of all chromosomes. Shown are the S. pennellii introgression regions for ILs covering chromosomes 1 to 12 (A-L) as determined by RESCAN. The depth of coverage (distance from midpoint on y-axis) and genotype (color and direction on y-axis) of each SNP/indel is plotted against chromosomal position (x-axis). Polymorphisms that match S. pennellii are colored green and plotted on the top half of each IL panel, while polymorphisms matching cv. M82 are plotted in magenta in the bottom halves. The coloring is on a continuum such that the color approaches black as a position’s genotype approaches heterozygosity. The y-axis tick marks indicate depths of coverage ranging from 0 to 20. Subsequent to genotyping, introgression boundaries consistent between the RNA-Seq and RESCAN analyses were delineated. Using these breakpoints, S. pennellii and cv. M82 regions are summarized by horizontal lines at the top and bottom of each IL panel, respectively.
tpc112391_Supplemental Figure 3.pdf
Supplemental Figure 4: Map of S. pennellii introgression lines, chromosomes 1-6.
Supplemental Figure 4: Map of S. pennellii introgression lines, chromosomes 1-6: A map showing the architecture of ILs based on precisely defined introgression boundaries determined from the sequenced tomato genome and next-generation sequencing data. IL size is proportional to the number of annotated genes harbored in each introgression. Bins, or intervals defined by unique combinations of IL overlap, are indicated with a “d-” prefix, indicating “Davis, CA,” to avoid confusion with previously designated bins. Regions of the genome not represented in the ILs are indicated by purple bars. Note that ILs can be non-contiguous (indicated by orange or yellow) as well as bins (indicated above graphs with arrowheads and lines). Only chromosomes 1-6 are shown for legibility. Chromosomes 7-12 are depicted in Supplemental Figure 5 online.
tpc112391_Supplemental Figure 4.pdf
Supplemental Figure 5: Map of S. pennellii introgression lines, chromosomes 7-12.
Supplemental Figure 5: Map of S. pennellii introgression lines, chromosomes 7-12: A map showing the architecture of ILs based on precisely defined introgression boundaries determined from the sequenced tomato genome and next-generation sequencing data. IL size is proportional to the number of annotated genes harbored in each introgression. Bins, or intervals defined by unique combinations of IL overlap, are indicated with a “d-” prefix, indicating “Davis, CA,” to avoid confusion with previously designated bins. Regions of the genome not represented in the ILs are indicated by purple bars. Note that ILs can be non-contiguous (indicated by orange or yellow) as well as bins (indicated above graphs with arrowheads and lines). IL9-3-1 posses introgressions on chromosomes 9 and 12, indicated by dashed double arrow. Only chromosomes 7-12 are shown for legibility. Chromosomes 1-6 are depicted in Supplemental Figure 4 online.
tpc112391_Supplemental Figure 5.pdf
Supplemental Figure 6: Distribution of genes per bin.
Supplemental Figure 6: Distribution of genes per bin. Histogram of the number of annotated genes per bin. A few bins possess over >1000 annotated genes, but a majority possess much less than 500. The mean bin size (in terms of annotated genes) is 177 genes, and the median size is 295.03 genes.
tpc112391_Supplemental Figure 6.pdf
Supplemental Figure 7: Z-score values of ILs relative to cv. M82.
Supplemental Figure 7: Z-score values of ILs relative to cv. M82: Z-score values of ILs (mean centered relative to cv. M82) for leaf development traits. Values are directional; yellow indicates standard deviations from cv. M82 towards S. pennellii, blue indicates transgressive standard deviations beyond cv. M82. Traits exhibit either broad deviation from cv. M82 towards S. pennellii values (e.g., leaf complexity traits) or more balanced deviation in both directions (e.g., cellular and stomatal traits, and leaflet AR and Roundness).
tpc112391_Supplemental Figure 7.pdf
Supplemental Figure 8: Correlation between leaf developmental traits.
Supplemental Figure 8: Correlation between leaf developmental traits: Shown is a matrix of correlation coefficient values between leaf development traits as measured in the ILs. Traits are arranged by similarity using absolute correlation from hierarchical clustering (bottom). Major groups of traits that vary similarly across the ILs include 1) leaflet size and leaf complexity traits, 2) pavement cell and stomatal patterning traits, and 3) traits relating to leaflet shape, serration, and flowering time. Developmentally relevant correlations include the negative correlation between leaflet size and leaf complexity and between pavement cell size and absolute stomatal density (Supplemental Figure 9 online). Blue indicates negative Pearson correlation coefficient values and yellow positive.
tpc112391_Supplemental Figure 8.pdf
Supplemental Figure 9: Broad-sense heritability for leaf developmental traits.
Supplemental Figure 9: Broad-sense heritability for leaf developmental traits: Colors denote traits with very high (red, H2 > 0.6), high (orange, 0.4 ≤ H2 < 0.6), intermediate (yellow, 0.2 ≤ H2 < 0.4), and low (green, H2 < 0.2) heritability values. All traits were measured under 2010 Davis, CA field conditions, unless otherwise noted (* denotes 2011 field data and § denotes cumulative data from 2010 – 2011). Generally, measures of leaflet serration, length-to-width ratio, and measures of shape (PCs 1 and 4) have high heritability, as does flowering time. Leaf complexity, other leaflet shape traits, and measures of leaflet size have intermediate heritability, whereas cellular and stomata traits have intermediate to low heritability.
tpc112391_Supplemental Figure 9.pdf
Supplemental Figure 10: Detected leaf development QTLs.
Supplemental Figure 10: Detected leaf development QTLs: p-values, as calculated from mixed-effect linear models for deviation of ILs from cv. M82. Shown are only those QTL with a significance value < 0.05. Yellow indicates deviation towards S. pennellii and blue indicates transgressive deviation beyond cv. M82. In total, 1035 QTL for leaf developmental traits were detected; 826 towards S. pennellii and 209 transgressive beyond cv. M82.
tpc112391_Supplemental Figure 10.pdf
Supplemental Figure 11: Leaflet shape QTL.
Supplemental Figure 11: Leaflet shape QTL: A) Mean terminal and distal lateral leaflet shapes for parents and ILs. Mean cv. M82 leaflet shapes are indicated in light gray, and mean shapes of S. pennellii, intermediate shape ILs towards S. pennellii (IL4-3 and IL5-4), and transgressive ILs beyond cv. M82 (IL2-1 and IL9-1-2) are shown as superimposed black outlines. S. pennellii leaflets exhibit an inverted length-to-width orientation relative to cv. M82; ILs 4-3 and 5-4 are similarly wider than cv. M82; and ILs 2-1 and 9-1-2 are significantly narrower than cv. M82. B) Shape QTL vary distinctly in the way they alter leaflet length-to-width ratios. Superimposed are the outlines of two intermediate, wider ILs (4-3 and 5-4) and two transgressive, narrower ILs (9-1-2 and 2-1). Note the distinctness of the tip and wider base of IL5-4 relative to IL4-3, and the more lanceolate shape of IL2-1 relative to IL9-1-2. C) PCs 1 and 4 (the most heritable PCs) differentiate the distinctness of shape ILs. PC1 explains variance due to length-to-width ratio differences, whereas PC4 explains the distribution of blade outgrowth along the proximal-distal axis of leaflet. ILs 2-1 and 5-4 vary most strongly with respect to PC4 (especially in the lateral leaflets), whereas ILs 4-3 and 9-1-2 are separated by PC1.
tpc112391_Supplemental Figure 11.pdf
Supplemental Figure 12: IL10-3 exhibits QTL affecting pavement cell size and stomatal density.
Supplemental Figure 12: IL10-3 exhibits QTL affecting pavement cell size and stomatal density. A) Images of epidermal peels from the adaxial side of mature leaves and cotyledons are shown. S. pennellii has larger pavement cells and decreased stomatal density relative to cv. M82, perhaps an adaptive feature to its native arid environment. IL10-3 exhibits decreased stomatal density on the adaxial side of mature leaves relative to cv. M82, and increased pavement cell size and decreased stomatal density on the adaxial side of cotyledons. B) IL10-3 is consistently one of the most extreme ILs for a suite of related traits, including adaxial leaf stomatal density, adaxial cotyledon stomatal density, and adaxial cotyledon pavement cell size. One perspective is that, because stomatal patterning in IL10-3 relative cv. M82 is not significantly changed, increases in pavement cell size decrease stomatal density.
tpc112391_Supplemental Figure 12.pdf
Supplemental Figure 13: Developmentally insightful correlations between leaf development traits.
Supplemental Figure 13: Developmentally insightful correlations between leaf development traits. A) Pairwise correlations between leaf size (“TermLfSize” and “LatLfSize”) and leaf complexity (“CompPri,” “CompInt,” “CompSec,” “CompRachis,” and “CompAll”). Besides the high correlations within leaf size and leaf complexity traits, there is significant negative correlation between size and complexity. The least significant negative correlation (LatLfSize x CompPri, r = -0.33) is significant at a level of p = 0.0046 (two-tailed, n = 72). The correlation suggests that overall blade area in a leaf is not modulated through complexity, as any additional leaflets are on average smaller. This has implications for resource allocation at the level of the leaf, but also between different parts of the plant, as complexity only modulates the dissection of the leaf rather than its overall blade area. B) Pairwise correlations between absolute stomatal density on the adaxial side of the cotyledon (“CotStom”) and epidermal pavement cell size (“CotPaveArea”) and count (“CotPaveCnt”). The negative correlation between CotStom and CotPaveArea, and the positive correlation between CotStom and CotPaveCnt, suggests that as pavement cell size increases, stomatal density decreases. The least significant correlation between two traits of each class (CotPaveArea x CotStom, r = -0.44) is significant at a level of p = 0.00011 (two-tailed, n = 72). This has implications for mechanisms by which stomatal spacing is modulated in this population, which may not be directly through stomatal patterning, but rather changes in epidermal pavement cell size.
tpc112391_Supplemental Figure 13.pdf
Supplemental Figure 14: Bin mapping and gene candidates.
Supplemental Figure 14: Bin mapping and gene candidates. A-D) Graphs showing select bin and IL mapping results for traits as indicated. Below the graph is an IL map for the region and trait. The size of ILs is proportional to the number of annotated genes that they possess. Colors indicate significance of detected QTL for trait values less than cv. M82 (blue) or greater than cv. M82 (yellow; see key, upper righthand corner). Above the IL map is indicated significance values from bin mapping. The height of a column within the bin region indicates the -log10(p-value) of the bin significance, and like ILs, the columns are appropriately colored. A) shows results for FlowTime, d-5E, B) LftAR, d-9B, C) LftAR, d-8F, D) CompAll, d-8A. See text for discussion of candidate genes regulating these traits. E) Annotated genes present in bin-5E. Chromosome position is indicated, as well as predicted genes and their orientation (red, forward; black, reverse orientation). On this short interval lies SP5G, a strong candidate regulating the flowering time QTL detected for this bin and perhaps a regulator of leaf morphology as well.
tpc112391_Supplemental Figure 14.pdf
Supplemental Figure 15: Bin mapping result legend.
Supplemental Figure 15: Bin mapping result legend. For each trait, bin and IL mapping results are visualized (Supplemental Figures 16–47 online). Below each graph is an IL map, the color of the ILs indicating the direction and significance of the QTL. Above this map is a graph, the height of the columns indicating the significance of the bin from the bin mapping results. Bin columns are colored based on their significance values. The y-axis indicates -log10(p-value). For both the IL map and bin mapping results graph, the size of bins and ILs is proportional to the number of annotated genes that they harbor.
tpc112391_Supplemental Figure 15.pdf
Supplemental Figure 16: Bin mapping results for CompAll.
Supplemental Figure 16: Bin mapping results for CompAll. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 16.pdf
Supplemental Figure 17: Bin mapping results for CompInt.
Supplemental Figure 17: Bin mapping results for CompInt. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 17.pdf
Supplemental Figure 18: Bin mapping results for CompPri.
Supplemental Figure 18: Bin mapping results for CompPri. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 18.pdf
Supplemental Figure 19: Bin mapping results for CompRachis.
Supplemental Figure 19: Bin mapping results for CompRachis. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 19.pdf
Supplemental Figure 20: Bin mapping results for CompSec.
Supplemental Figure 20: Bin mapping results for CompSec. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 20.pdf
Supplemental Figure 21: Bin mapping results for CotPaveAR.
Supplemental Figure 21: Bin mapping results for CotPaveAR. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 21.pdf
Supplemental Figure 22: Bin mapping results for CotPaveArea.
Supplemental Figure 22: Bin mapping results for CotPaveArea. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 22.pdf
Supplemental Figure 23: Bin mapping results for CotPaveCirc.
Supplemental Figure 23: Bin mapping results for CotPaveCirc. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 23.pdf
Supplemental Figure 24: Bin mapping results for CotPaveCnt.
Supplemental Figure 24: Bin mapping results for CotPaveCnt. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 24.pdf
Supplemental Figure 25: Bin mapping results for CotPaveRound.
Supplemental Figure 25: Bin mapping results for CotPaveRound. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 25.pdf
Supplemental Figure 26: Bin mapping results for CotPaveSolid.
Supplemental Figure 26: Bin mapping results for CotPaveSolid. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 26.pdf
Supplemental Figure 27: Bin mapping results for CotStom.
Supplemental Figure 27: Bin mapping results for CotStom. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 27.pdf
Supplemental Figure 28: Bin mapping results for CotStomInd.
Supplemental Figure 28: Bin mapping results for CotStomInd. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 28.pdf
Supplemental Figure 29: Bin mapping results for FlowTime.
Supplemental Figure 29: Bin mapping results for FlowTime. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 29.pdf
Supplemental Figure 30: Bin mapping results for LatLfSize.
Supplemental Figure 30: Bin mapping results for LatLfSize. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 30.pdf
Supplemental Figure 31: Bin mapping results for LatPC1.
Supplemental Figure 31: Bin mapping results for LatPC1. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 31.pdf
Supplemental Figure 32: Bin mapping results for LatPC2.
Supplemental Figure 32: Bin mapping results for LatPC2. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 32.pdf
Supplemental Figure 33: Bin mapping results for LatPC3.
Supplemental Figure 33: Bin mapping results for LatPC3. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 33.pdf
Supplemental Figure 34: Bin mapping results for LatPC4.
Supplemental Figure 34: Bin mapping results for LatPC4. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 34.pdf
Supplemental Figure 35: Bin mapping results for LatPC5.
Supplemental Figure 35: Bin mapping results for LatPC5. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 35.pdf
Supplemental Figure 36: Bin mapping results for LfAbStom.
Supplemental Figure 36: Bin mapping results for LfAbStom. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 36.pdf
Supplemental Figure 37: Bin mapping results for LfAdStom.
Supplemental Figure 37: Bin mapping results for LfAdStom. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 37.pdf
Supplemental Figure 38: Bin mapping results for LfStomRatio.
Supplemental Figure 38: Bin mapping results for LfStomRatio. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 38.pdf
Supplemental Figure 39: Bin mapping results for LftAR.
Supplemental Figure 39: Bin mapping results for LftAR. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 39.pdf
Supplemental Figure 40: Bin mapping results for LftCirc.
Supplemental Figure 40: Bin mapping results for LftCirc. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 40.pdf
Supplemental Figure 41: Bin mapping results for LftRound.
Supplemental Figure 41: Bin mapping results for LftRound. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 41.pdf
Supplemental Figure 42: Bin mapping results for LftSolid.
Supplemental Figure 42: Bin mapping results for LftSolid. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 42.pdf
Supplemental Figure 43: Bin mapping results for TermLfSize.
Supplemental Figure 43: Bin mapping results for TermLfSize. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 43.pdf
Supplemental Figure 44: Bin mapping results for TermPC1.
Supplemental Figure 44: Bin mapping results for TermPC1. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 44.pdf
Supplemental Figure 45: Bin mapping results for TermPC3.
Supplemental Figure 45: Bin mapping results for TermPC3. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 45.pdf
Supplemental Figure 46: Bin mapping results for TermPC4.
Supplemental Figure 46: Bin mapping results for TermPC4. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 46.pdf
Supplemental Figure 47: Bin mapping results for TermPC5.
Supplemental Figure 47: Bin mapping results for TermPC5. See Supplemental Dataset 7 online for trait details and Supplemental Figure 15 online for legend.
tpc112391_Supplemental Figure 47.pdf
Supplemental Figure 48: Significant correlations between leaf complexity and shape with fruit sugar levels.
Supplemental Figure 48: Significant correlations between leaf complexity and shape with fruit sugar levels. The traits Brix (BX), glucose, maltose, fructose, sucrose, and glucose_e were graphed as a function of the leaf morphology traits A) CompAll, a measure of overall leaf complexity, B) LatPC4 (PC4 values for lateral leaflets), and C) TermPC4 (PC4 values for terminal leaflets). Trait values are given as averaged z-scores, mean-centered on the cv. M82 value. To aid the visualization of the correlations, fitted linear (yellow) and LOESS (blue) models are provided. p-values, multiple test adjusted for all trait x trait correlations, are given. D) Examples of differences in leaf complexity, with which fruit sugar levels positively correlate with, amongst ILs. Shown are ILs with significantly decreased (IL7-4-1) and increased (IL8-2) complexity relative to cv. M82. CompAll values are the sum of primary, intercalary (purple), and secondary (orange) leaflet counts. E) Examples of differences in PC4-related leaflet shape variance, with which fruit sugar levels negatively correlate. Shown are ILs with significantly decreased (IL1-1) and increased (IL8-1-1) PC4 values.
tpc112391_Supplemental Figure 48.pdf
Supplemental Figure 49: Network analysis reveals a relationship between leaf complexity and shape with sugars, Brix, and biomass.
Supplemental Figure 49: Network analysis reveals a relationship between leaf complexity and shape with sugars, Brix, and biomass. A) Hive plot axis with significant correlations (after multiple test adjustment) between DEV traits and traits from other classes arranged by -log10(p-value). Each edge represents such a correlation, and is colored by -log10(p-value): ≥ 3.0 black, ≥ 2.0 blue, < 2.0 yellow. B) The other hive plot axis, in which nodes correspond to traits from the MET, ENZ, MOR, and SEED trait classes, arranged by the overall connectivity of the trait. Additionally, the size of the terminal end of each edge is proportional to the trait connectivity. Note that the most significant correlations tend to involve traits with high connectivity. C) Traits with the highest connectivities along the axis in (B) are shown. Adjacent to each trait is a dot representing the trait class (MOR magenta, MET blue, ENZ yellow, and SEED orange). The traits with the highest connectivity include traits associated with either vegetative biomass or fruit mono- and disaccharide levels. D) Traits representing the most significant correlations are shown. There is an abundance of correlations between leaf complexity traits (“Comp” traits) and PC4 with biomass and mono- and disaccharide level traits. The correlations of interest are denoted by an asterisk.
tpc112391_Supplemental Figure 49.pdf
Supplemental Figure 50: Hierarchical clustering of traits analyzed in this study.
Supplemental Figure 50: Hierarchical clustering of traits analyzed in this study. Hierarchical clustering of leaf development traits with other previously studied traits. Hierarchical clustering is based on absolute correlation values. This figure complements Figure 4 to show trait names. Traits are represented by their class followed by their name. Trait classes are represented by color: Black, “DEV”; magenta, “MOR”; blue, “MET”; yellow, “ENZ”; orange, “SEED”. The group of traits, including PW, BX, EA, glucose, galactose, fructose, sucrose, mannose, and trehalose, that are mentioned in the text can be found in the uppermost cluster indicated by the red dotted box. The groups of traits corresponding to the upper right hand dotted box in Fig. 4A are indicated in the lower part of this figure, also with a dotted, black box. This constellation of traits negatively correlates with harvest index (HI), many of which involve amino acid metabolism (indicated by asterisk).
tpc112391_Supplemental Figure 50.pdf
Supplemental Figure 51: Jackknifing results indicate stable correlations between leaf complexity and shape with sugar metabolism and yield traits.
Supplemental Figure 51: Jackknifing results indicate stable correlations between leaf complexity and shape with sugar metabolism and yield traits. A) Visualization of a sampling of jackknifing results (from Supplemental Dataset 12 online) for significant correlations between leaf complexity and shape traits with yield-associated and sugar metabolite traits. The small black dot represents the actual value of the Pearson correlation coefficient between the two traits indicated on the x-axis. Bars represent the standard error of jackknifing results. The larger, transparent orange dot represents the actual r value plus the calculated jackknifed bias. B) The same results indicated in (A), but showing individual calculated r values from the removal of each IL. Large black dot represents the actual r value, the large transparent orange dot represents r plus the jackknife bias, and the small blue dots represent individual jackknifed values that were used to calculate standard error and jackknifed bias. Note the relative stability of r values to the removal of IL values calculating the correlation between traits, indicating that significant r values do not represent undue bias from a few ILs.
tpc112391_Supplemental Figure 51.pdf
Supplemental Figure 52: Traits significantly correlated with a distinct cluster of genes.
Supplemental Figure 52: Traits significantly correlated with a distinct cluster of genes. A histogram of the traits significantly correlated with the group of genes forming a distinct cluster marked by “*” in Figure 5A. Classes of traits are denoted by color (“DEV”, black; “ENZ”, yellow; “MET”, blue; “MOR”, magenta; and “SED”, orange). Note the preponderance of traits of the “DEV” class concerning leaf development phenotypes. The most abundant trait correlating with this group of genes of a class other than “DEV” is glucose levels (“MET”) in the fruit pericarp.
tpc112391_Supplemental Figure 52.pdf
Supplemental Table 1: Summary of cv. M82 vs. S. pennellii SNP/indel distribution for RNAseq and RESCAN analyses.
Supplemental Table 1: Summary of cv. M82 vs. S. pennellii SNP/indel distribution for RNAseq and RESCAN analyses. Provided are the summary statistics for base pairs and genes between SNPs and indels derived from RNA-Seq, RESCAN, and combined RNA-Seq and RESCAN datasets.
tpc112391_Supplemental Table 1.xls
Supplemental Table 2: Chromosomal positions of the S. pennellii introgression boundaries for all 76 ILs.
Supplemental Table 2: Chromosomal positions of the S. pennellii introgression boundaries for all 76 ILs. Boundaries were deduced by combining RNAseq and RESCAN analyses and are represented graphically in Supplemental Figure 1 online. The last cv. M82 polymorphism position preceding the introgression (“M82 (last)”) and the first cv. M82 polymorphism following (“M82 (first)”) are provided, in addition to the first (“PEN (first)”) and last (“PEN (last)”) S. pennellii polymorphism. “-1” indicates that the S. pennellii genotype extends to the beginning or end of a chromosome.
tpc112391_Supplemental Table 2.xls
Supplemental Dataset 1: Polymorphism database.
Supplemental Dataset 1: Polymorphism database. A set of flat-file databases of polymorphisms identified between cv. M82 and S. pennellii using RNA-Seq (SNPs/indels) or RESCAN (SNPs) sequence data. Column titles: (1) chromosome, (2) position, (3) reference base, (4) SNP base, (5) genotype SNP/indel in which SNP/indel was identified, (6) insert position.
tpc112391_Supplemental Dataset 1.zip
Supplemental Dataset 2: Unique IL combinations define bins.
Supplemental Dataset 2: Unique IL combinations define bins. Provided is a binary matrix showing the combinations of ILs (top row) that define unique bins (left column). “1” indicates that the given bin is defined by the presence of the corresponding IL, whereas “0” indicates that the bin is defined by the absence of the IL.
tpc112391_Supplemental Dataset 2.xls
Supplemental Dataset 3: Genes per bin.
Supplemental Dataset 3: Genes per bin. A list of the number of annotated genes present within each bin.
tpc112391_Supplemental Dataset 3.xls
Supplemental Dataset 4: Annotation of genes present in each bin.
Supplemental Dataset 4: Annotation of genes present in each bin. Provided is a list of annotated genes in the tomato genome. For each gene, the chromosome (“chromosome”) and bin (“bin”) within which it resides is given. “Subset.bin” indicates the specific sub-bin (if the bin is non-contiguous) within which the gene resides. “Gap” indicates that the gene is not represented by any IL. Also shown is the beginning (“begin”) and ending (“end”) coordinates of the gene in the tomato genome, the linear order of genes in the genome (“sort.order”), a description of the gene (“Human.readable.description”), the best BLAST Arabidopsis hit (“Subject.ID”, “AGI”), a description of the best Arabidopsis hit (“Description”), as well as BLAST hit statistics (“Score,” “E.Value,”, and “Identities”).
tpc112391_Supplemental Dataset 4.xls
Supplemental Dataset 5: Modeled trait values and significance values.
Supplemental Dataset 5: Modeled trait values and significance values. For each trait studied, the model-fitted deviation for each IL from the estimated cv. M82 value is given (under the column “Estimate”). Additionally, standard error (“SE”), t-values (“t.value), and p-values (“p.value”) for the estimates are provided.
tpc112391_Supplemental Dataset 5.xls
Supplemental Dataset 6: Graphs of fitted values for each trait, their distributions, and significance values.
Supplemental Dataset 6: Graphs of fitted values for each trait, their distributions, and significance values. Provided is a graph corresponding to each trait. The x-axis of each graph is IL identity, and the y-axis represents modeled trait values for each IL. Modeled trait values are expressed as deviation from cv. M82, which by definition is set to “0” and represented by a bold horizontal line. For each IL, its modeled value is accompanied by standard error bars. Additionally, p-values representing significant deviation from cv. M82 are denoted by color. Red, p < 0.0001; orange, 0.0001 ≤ p < 0.001; yellow, 0.001 ≤ p < 0.01; green, 0.01 ≤ p < 0.05. Trait values represent transformed values, as indicated in Supplemental Dataset 7 online.
tpc112391_Supplemental Dataset 6.pdf
Supplemental Dataset 7: Descriptions of traits and modeling.
Supplemental Dataset 7: Descriptions of traits and modeling. Following the abbreviation for each trait, which is used in the main text and figures, is a description of the trait. Information relating to the statistical modeling of each trait is given, including any transformation that was used, units measured and their conversions, a description of pseudoreplication, and a qualitative interpretation of what the values of the trait represent. Following this description is a list of significant factors that were used in the modeling of the trait and their associated p-values. If a mixed-effect linear model was used, fixed effects are denoted by “[fixed]” and all other factors were treated as random. If there were no significant random effects, ANOVA modeling was used and besides the one factor modeled, “(no other factors significant)” is denoted.
tpc112391_Supplemental Dataset 7.xls
Supplemental Dataset 8: Traits used from other studies.
Supplemental Dataset 8: Traits used from other studies. A list of traits meta-analyzed in this study. Traits are assigned to classes: “ENZ,” enzymatic activity measured from the fruit pericarp (Steinhauser et al., 2011); “MET,” metabolite levels from the fruit pericarp (Schauer et al., 2006; Schauer et al., 2008); “MOR,” yield, biomass, and morphological traits (Schauer et al., 2006; Schauer et al., 2008); “SEED,” seed metabolite levels (Toubiana et al., 2012). In addition to the trait abbreviation, for “MOR” traits a brief description is given; for all other traits, the abbreviation roughly corresponds to the metabolite or enzymatic activity measured, and precise definitions for all traits can be found from their publically-available source: phenome-networks.com. The “studies” for which the raw data is derived from phenome-networks.com is also given: A = akko 2001 II, B = akko 2001 met, C = akko 2001 metabolites A, D = akko 2001 metabolites B, M = akko 2003 metabolites A, N = akko 2003 metabolites B, O = akko 2003 enzymes, P = akko 2003, W = akko 2004 enzymes, X = akko 2004 morphology, Y = akko 2004 seed metabolites, Z = akko 2004 metabolites. Only homozygous IL traits were considered. For some traits there was a deficit in the ILs measured, and to not bias inter-trait analyses, only those traits for which > 60 ILs (not including cv. M82) were measured were included (practically, the trait with the fewest ILs measured after this condition has 67 IL values). Whether the trait was “included” or “dropped” from analyses in this study is given in the “Included.Dropped” column.
tpc112391_Supplemental Dataset 8.xls
Supplemental Dataset 9: Matrix of averaged z-scores.
Supplemental Dataset 9: Matrix of averaged z-scores. A matrix of the averaged z-score values for each trait across measured ILs. These values represent an averaging of z-score normalized trait values for ILs (mean centered relative to cv. M82) across the replicates available for each trait. Traits are identified by their trait class followed by trait name. NA = “not available.”
tpc112391_Supplemental Dataset 9.xls
Supplemental Dataset 10: Pair-wise Pearson correlation coefficient values between traits.
Supplemental Dataset 10: Pair-wise Pearson correlation coefficient values between traits. Pair-wise correlation coefficients between traits of all classes (“DEV,” “MOR,” “MET,” “ENZ,” and “SED”). Given are the classes and names of each trait pair and their correlation coefficient.
tpc112391_Supplemental Dataset 10.xls
Supplemental Dataset 11: Significance values for pair-wise correlations between traits.
Supplemental Dataset 11: Significance values for pair-wise correlations between traits. Significance values given for the pair-wise correlations between traits of all classes (“DEV,” “MOR,” “MET,” “ENZ,” and “SED”). Given is the p-value of the correlation (calculated with n representing the number of correlated data points, adjusting for missing data). Adjusted p-values, using the Benjamini and Hochberg method to control for false discovery rate, are also given (Benjami and Hochberg, 1995). Additionally, the “sig.DEV.interact” column indicates those correlations between a “DEV” trait and a trait of another trait class besides “DEV” that is significant after multiple test adjustment.
tpc112391_Supplemental Dataset 11.xls
Supplemental Dataset 12: Jackknifing results for significant correlations between DEV and traits of other classes.
Supplemental Dataset 12: Jackknifing results for significant correlations between DEV and traits of other classes. A table of jackknifing results: only those correlations between a DEV trait and a trait of a different class that was significant after multiple test correction was considered. Given is the class of each trait, name, p-value of the Pearson correlation coefficient, the adjusted p-value, and value of r. For each instance of removing a single data point, the standard error of the resulting jackknifed distribution, the bias, and the jackknifed correlation coefficients used to compute standard error and bias (as a series of columns labeled “jack.result”) is given.
tpc112391_Supplemental Dataset 12.xls
Supplemental Dataset 13: IL expression values for genes residing on chromosomes 1-3 and unassembled genes.
Supplemental Dataset 13: IL expression values for genes residing on chromosomes 1-3 and unassembled genes. A table of averaged normalized expression values (in reads per million) in the vegetative apex for genes on chromosomes 1-3 (and unassembled genes). See Materials and Methods for details.
tpc112391_Supplemental Dataset 13.xls
Supplemental Dataset 14: IL expression values for genes residing on chromosomes 4-8.
Supplemental Dataset 14: IL expression values for genes residing on chromosomes 4-8. A table of averaged normalized expression values (in reads per million) in the vegetative apex for genes on chromosomes 4-8. See Materials and Methods for details.
tpc112391_Supplemental Dataset 14.xls
Supplemental Dataset 15: IL expression values for genes residing on chromosomes 9-12.
Supplemental Dataset 15: IL expression values for genes residing on chromosomes 9-12. A table of averaged normalized expression values (in reads per million) in the vegetative apex for genes on chromosomes 9-12. See Materials and Methods for details.
tpc112391_Supplemental Dataset 15.xls
Supplemental Dataset 16: Gene expression profiles significantly correlated with traits.
Supplemental Dataset 16: Gene expression profiles significantly correlated with traits. A table of genes, of which their expression profile across ILs significantly correlates with measured IL trait values (after multiple test adjustment). For each significant correlation, the gene, trait, and slope and p-value resulting from linear modeling are provided. The multiple test adjusted p-value (as determined using the BH method) is also shown. The bin to which each gene belongs and gene annotation information is also given.
tpc112391_Supplemental Dataset 16.xls
Supplemental Dataset 17: A group of genes with similar expression profiles.
Supplemental Dataset 17: A group of genes with similar expression profiles. A list of genes belonging to the cluster marked by “*” in Figure 5A. The chromosome and bin within which the genes reside is provided, as well as annotation information. As the expression profiles of these genes correlate with a preponderance of leaf development traits (see Supplemental Figure 52 online), it is not surprising that a number of developmental genes are present in this list (as described in the text). However, these genes are also enriched for photosynthetic functions, as revealed by GO enrichment analysis (Supplemental Dataset 18 online).
tpc112391_Supplemental Dataset 17.xls
Supplemental Dataset 18: GO categories enriched for a group of genes with distinct expression profiles.
Supplemental Dataset 18: GO categories enriched for a group of genes with distinct expression profiles. A list of significantly enriched GO categories for the group of genes indicated by “*” in Figure 5A and listed in Supplemental Dataset 17 online. The GO categories shown are significantly enriched at a p-value < 0.05, as multiple test adjusted using the BH method. Note the abundance of categories related to photosynthetic-related functions.
tpc112391_Supplemental Dataset 18.xls
Supplemental Dataset 19: Seed sources used in this study.
Supplemental Dataset 19: Seed sources used in this study. For each IL, the original source of seed is provided. Germplasm was derived from two separate gifts from Dani Zamir (Hebrew University, Rehovot, Israel), denoted Zamir I and Zamir II, and the Tomato Genetics Resource Center (U.C. Davis), denoted TGRC.
tpc112391_Supplemental Dataset 19.xls