DOI: 10.5061/dryad.rm5v5
title: Data from: A quantitative genetic basis for leaf morphology in a set of precisely defined tomato introgression lines

description: 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.
description: 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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 &gt;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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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 &gt; 0.6), high (orange, 0.4 ≤ H2 &lt;
 0.6), intermediate (yellow, 0.2 ≤ H2 &lt; 0.4), and low (green, H2 &lt;
 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.pdfSupplemental 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 &lt; 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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, &lt; 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.pdfSupplemental 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.xlsSupplemental 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.xlsSupplemental 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.zipSupplemental 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.xlsSupplemental 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.xlsSupplemental 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.xlsSupplemental 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.xlsSupplemental 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 &lt; 0.0001; orange, 0.0001 ≤ p &lt;
 0.001; yellow, 0.001 ≤ p &lt; 0.01; green, 0.01 ≤ p &lt; 0.05. Trait
 values represent transformed values, as indicated in Supplemental Dataset
 7 online.tpc112391_Supplemental Dataset
 6.pdfSupplemental 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.xlsSupplemental 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 &gt; 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.xlsSupplemental 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.xlsSupplemental 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.xlsSupplemental 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.xlsSupplemental 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.xlsSupplemental 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.xlsSupplemental 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.xlsSupplemental 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.xlsSupplemental 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.xlsSupplemental 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.xlsSupplemental 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
 &lt; 0.05, as multiple test adjusted using the BH method. Note the
 abundance of categories related to photosynthetic-related
 functions.tpc112391_Supplemental Dataset
 18.xlsSupplemental 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