# Source paper archive - Source title: The genetic basis of extra-lobed leaves in ivyleaf morning glory (Ipomoea hederacea) - Author(s): Henry, M. R., Hernandez, D. J., Li, M., Glasgow, E., Peake, A. L., Stinchcombe, J. R. - Source landing URL: https://www.biorxiv.org/content/10.64898/2026.10.27.762295v1 - PDF URL: https://www.biorxiv.org/content/10.64898/2026.10.27.762295v1.full.pdf - PDF SHA-256: b71f1518951b88f81b1f977cd68ea332e665bff6147eccc8910ce5f0412dc5d7 - Converter: pymupdf4llm 0.0.27 - Limits: Automated PDF text extraction; reading order, equations, tables and formatting may be incomplete or incorrect. Images are omitted, and no OCR was performed. Markup and links are neutralized for safe downloading. Consult the original PDF for the authoritative version. --- [bioRxiv preprint doi: https://doi.org/10.64898/2026.10.27.762295; this version posted November 2, 2026. The copyright holder for this preprint](https://doi.org/10.64898/2026.10.27.762295) (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made [available under a CC-BY-NC-ND 4.0 International license.](http://creativecommons.org/licenses/by-nc-nd/4.0/) 1 **Title:** The genetic basis of extra-lobed leaves in ivyleaf morning glory ( _Ipomoea hederacea_ ) 2 **Authors:** Martin R. Henry [1,2], Damian J. Hernandez [1], Margaret C. Li [1], Emily Glasgow [1], Amanda L. Peake [1], 3 John R. Stinchcombe [1 ] 4 1 Department of Ecology and Evolutionary Biology, University of Toronto 5 25 Willcocks Street, Room 3055, Toronto, Ontario, Canada, M5S 3B2 6 2 Martin.henry@mail.utoronto.ca 7 **Keywords** : leaf shape, bulked segregant analysis, leaf lobing, QTLseqr, QTL 8 9 **[Author Contributor Roles Taxonomy:](https://credit.niso.org/)** 10 **MRH:** Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Project 11 Administration, Software, Supervision, Visualization, Writing- Original Draft Preparation, Writing 12 Review and Editing 13 **DJH:** Data Curation, Formal Analysis, Investigation, Methodology, Software, Validation, Writing - Review 14 and Editing 15 **MCL:** Investigation, Writing - Review & Editing 16 **EG:** Investigation, Resources, Writing - Review & Editing 17 **ALP:** Investigation, Methodology, Software, Writing - Review and Editing 18 **JRS:** Conceptualization, Funding Acquisition, Investigation, Project Administration, Resources, 19 Supervision, Writing - Original Draft Preparation, Writing - Review and Editing 20 21 **ORC-IDs:** 22 **MRH:** 0009-0007-4050-2493 23 **DJH:** 0000-0001-9833-1155 24 **MCL:** 0009-0007-2310-133X 25 **EG:** 0009-0000-3637-7510 26 **ALP:** 0009-0003-1512-1008 27 **JRS:** 0000-0003-3349-2964 [bioRxiv preprint doi: https://doi.org/10.64898/2026.10.27.762295; this version posted November 2, 2026. The copyright holder for this preprint](https://doi.org/10.64898/2026.10.27.762295) (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made [available under a CC-BY-NC-ND 4.0 International license.](http://creativecommons.org/licenses/by-nc-nd/4.0/) 28 # Article summary 29 Ivyleaf morning glory exhibits two main leaf shapes, heart-shaped entire leaves and 3-lobed, controlled 30 by a single Mendelian locus. However, within the lobed genotypes, there are occasional individuals that 31 produce leaves with extra lobes. We examined whether there was a simple genetic basis to producing 32 extra lobes, and if so, does it have the same genetic basis as the other leaf shapes, or are different 33 regions in the genome responsible? After planting 500 individuals in a greenhouse and collecting 34 phenotypic and genomic data, we found that extra-lobing is heritable, does not have a simple 35 Mendelian basis, but may be influenced by multiple QTLs. 36 # 37 Abstract 38 Intraspecific leaf shape variation is common among angiosperms. Ivyleaf morning glory ( _Ipomoea_ 39 _hederacea_ ) has become a useful system for studying the genetics and ecology of leaf shape variation as 40 this species exhibits two leaf shapes: leaves with entire margins, and 3-lobed leaves. It is known that 41 these phenotypes are controlled by a single locus, and differ in their ecophysiology, geographic 42 distribution, ecology, and fitness. However, while lobed individuals producing leaves with 1-2 extra lobes 43 have also been regularly observed, the genetic basis, if any, of these phenotypes has not been 44 described. To investigate the genetic basis of extra-lobing, we compared phenotypic distributions of leaf 45 shapes of an F2 generation to Mendelian ratios for a single locus trait and conducted a bulked segregant 46 analysis to uncover quantitative trait loci. Our results suggest that producing extra-lobed leaves has a 47 complex genetic basis and that there are multiple QTLs underlying this phenotype containing potential 48 candidate genes involved with auxin distribution and leaf development. Whether these extra-lobed 49 phenotypes also differ in terms of their physiology and ecology remains unexplored. [bioRxiv preprint doi: https://doi.org/10.64898/2026.10.27.762295; this version posted November 2, 2026. The copyright holder for this preprint](https://doi.org/10.64898/2026.10.27.762295) (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made [available under a CC-BY-NC-ND 4.0 International license.](http://creativecommons.org/licenses/by-nc-nd/4.0/) # 50 Introduction 51 Leaves display tremendous diversity across angiosperms. Leaves broadly fall into two general categories: 52 simple (e.g., _Arabidopsis thaliana_ ) or compound (having multiple small leaflets per leaf; e.g., _Solanum_ 53 _lycopersicum_ ). Leaves can also be further described as having entire (smooth) or non-entire (e.g. 54 serrated, lobed, etc.) margins. Variation in leaf morphology including leaf dissection, marginal 55 structures, size, thickness, venation, and trichome density influence how plants photosynthesize, 56 intercept light, regulate heat, support the leaf structure, use water efficiently, and avoid herbivory 57 (Brown et al. 1991; Givnish 1979; Nicotra et al. 2011; Vogel 1970). Here, we investigate the genetic basis 58 of a previously uncharacterized leaf shape phenotype in ivyleaf morning glory ( _Ipomoea hederacea_ ), 59 identifying multiple QTLs associated with the production of four and five lobed leaves, including regions 60 that contain candidate genes involved with auxin distribution and leaf development. 61 62 Intraspecific leaf shape variation is common, and it is often assumed that differences in leaf shape are 63 ecologically important adaptations to differences in environmental conditions across a species range 64 (Givnish 1987). For example, leaf shape in butterfly weed ( _Asclepias tuberosa_ ) differs between eastern 65 and western populations, and this difference was correlated with moisture stress (Wyatt and Antonovics 66 1981). Red maple ( _Acer rubrum_ ) leaves were found to be more dissected and toothed at colder 67 locations, and California black oak ( _Quercus kelloggii_ ) leaves were also more toothed with smaller leaf 68 areas at higher elevations (Royer et al. 2008). In addition, _Mimulus laciniatus_ was also shown to have 69 more deeply lobed leaves at higher elevations (Love and Ferris 2024). Some studies have found that leaf 70 shape appears to be under selection, but few have demonstrated a clear selective agent (Bright and 71 Rausher 2008; Campitelli and Stinchcombe 2013; Ferris and Willis 2018; Nagy 1997; Richards et al. 72 2019). One challenge is that leaf shape may be correlated with other functional traits that are the actual 73 targets of selection (Nagy 1997). Identifying the genetic basis of leaf shape variation may help clarify 74 whether selection is acting directly on the loci responsible for shape itself, correlated pleiotropic effects 75 of anatomical or physiological consequences of leaf shape, or traits that are genetically linked to leaf 76 shape loci (Peake et al. 2026). 77 78 Leaf shape is the outcome of a complex interaction between hormonal physiology, genetics, and 79 environmental factors. Leaves begin as leaf primordia on the shoot apical meristem where high auxin 80 concentrations are generated by PIN-FORMED (PIN) auxin efflux carrier proteins (Benková et al. 2003; [bioRxiv preprint doi: https://doi.org/10.64898/2026.10.27.762295; this version posted November 2, 2026. The copyright holder for this preprint](https://doi.org/10.64898/2026.10.27.762295) (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made [available under a CC-BY-NC-ND 4.0 International license.](http://creativecommons.org/licenses/by-nc-nd/4.0/) 81 Heisler et al. 2005; Petrášek et al. 2006; Scarpella et al. 2010). The leaf will then undergo primary 82 morphogenesis, beginning with the critical establishment of the adaxial-abaxial, or upper and lower, leaf 83 identities. Marginal structures such as serrations and lobes develop early on in areas of high auxin 84 concentration driven by PIN1-dependant polar auxin transport, in conjunction with CUP-SHAPED 85 COTYLEDON (CUC) transcription factors and microRNA (miRNA) coordination in the leaf sinuses 86 (Benková et al. 2003; Bilsborough et al. 2011; Nikovics et al. 2006). In secondary morphogenesis the leaf 87 has its basic shape, but its ultimate form will come from cellular expansion, and the development of 88 mature vasculature and epidermal cell types such as guard cells and trichomes (Efroni et al. 2010; Kalve 89 et al. 2014). The development of more complex leaves (i.e. more leaflets, deeper lobes, etc.) is in part 90 due to prolonged cell proliferation and expansion in localized areas on the leaf margin (Barth et al. 2009; 91 Hagemann and Gleissberg 1996; Ori et al. 2007). Most angiosperm leaves are determinate structures 92 and will eventually cease growth to achieve a final shape and size. 93 94 _Ipomoea hederacea_ (L.) Jaquin (Convolvulaceae) shows a well-known Mendelian polymorphism for leaf 95 shape (3-lobed versus heart-shaped, entire leaves; Figure 1) that appears to be under selection and 96 follows a latitudinal cline (Bright and Rausher 2008; Bright-Emlen 1998; Campitelli and Stinchcombe 97 2013; Elmore 1986). However, it is not uncommon to observe lobed genotypes producing leaves with 98 either 4 or 5 lobes (Figure 1). The phenotype is only observed in the lobed genetic background, 99 suggesting either genotype by environment or epistatic interactions between the Mendelian leaf shape 100 locus and unknown loci and/or environmental cues. While the genetics, ecology, and evolution of the 3 101 lobed polymorphism has been intensely investigated (Boyle et al. 2024; Bright and Rausher 2008; Bright 102 Emlen 1998; Campitelli et al. 2008, 2013; Campitelli and Stinchcombe 2013, 2014; Elmore 1986; Ennos 103 1981; Hull-Sanders et al. 2005; Peake et al. 2026; Singhal et al. 2025; Stinchcombe 2002; Stinchcombe et 104 al. 2001), the ecological significance and the genetic basis of the extra-lobed phenotype remains 105 unknown. [bioRxiv preprint doi: https://doi.org/10.64898/2026.10.27.762295; this version posted November 2, 2026. The copyright holder for this preprint](https://doi.org/10.64898/2026.10.27.762295) (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made [available under a CC-BY-NC-ND 4.0 International license.](http://creativecommons.org/licenses/by-nc-nd/4.0/) 106 107 Figure 1: Leaf shape in _I. hederacea_ : entire, 3-lobed, weakly 4-lobed, 4-lobed, weakly 5-lobed, fully 5-lobed (from 108 left to right, top to bottom). Drawing by Martin Rose Henry. 109 110 In this study, we examined the genetic basis of extra-lobing in _I. hederacea_ using a combination of 111 controlled crosses and next-generation bulked segregant analysis (BSA). We identified quantitative trait 112 loci (QTLs) that are associated with the extra-lobed phenotype using a BSA. Additionally, we mapped _I._ 113 _hederacea_ genes to _A. thaliana_ and _S. lycopersicum_ reference genome annotations to determine which 114 genes and protein functions are present in significantly different QTL regions. We also conducted a gene 115 ontology (GO) enrichment analysis to identify putative functions that are more strongly enriched in 116 extra-lobed plants relative to 3-lobed plants. With the combination of gene identification through 117 genome-wide protein alignments and GO enrichment, we identified potentially important genes 118 underlying the extra-lobed phenotype in ivyleaf morning glory. 119 [bioRxiv preprint doi: https://doi.org/10.64898/2026.10.27.762295; this version posted November 2, 2026. The copyright holder for this preprint](https://doi.org/10.64898/2026.10.27.762295) (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made [available under a CC-BY-NC-ND 4.0 International license.](http://creativecommons.org/licenses/by-nc-nd/4.0/) # 120 Materials and Methods ## 121 Species description 122 Ivyleaf morning glory, _I. hederacea_, is a weedy annual flowering vine found in eastern North America. It 123 inhabits disturbed sites, roadside ditches, and crop fields (Bright-Emlen 1998; Mohr 1901; Shreve et al. 124 1910; Stevens 1948). Ivyleaf morning glory frequently self-pollinates, with selfing rates of up to 93% in 125 some populations (Campitelli and Stinchcombe 2014; Ennos 1981). ## 126 Crossing design, greenhouse methods, and phenotyping 127 We planted 500 F 2 individuals derived from a cross between a 3-lobed individual and an individual 128 regularly producing 5-lobed leaves. Parental lines had been collected from Delaware [39.721049 °N, 129 75.745283 °W] and Maryland [38.83662 °N, -76.07692°W] respectively, and had been self-fertilized for 3 130 generations prior to the cross. We allowed a single F 1 individual to self-fertilize to produce F 2 131 experimental seeds. We then grew F 2 plants in 26 cm [3] tree pots and top watered them until they 132 germinated. Benches were then flooded on a 6-hour schedule, with a 16-hour daylength and at 26-30°C˚. 133 Further details on growth conditions are in Supplementary Materials. 134 135 After one month, we scored the leaf shape phenotype for each plant over three days. We scored plants 136 as: 3-lobed; 4-lobed if they had at least one leaf with an extra lobe; 4- and 5-lobed if they had at least 137 one of each; and 5-lobed if they had at least one leaf with 5-lobes, but no 4-lobed leaves. ## 138 DNA extraction and genomic sequencing 139 We sampled small, fresh leaves for DNA extraction from 142 of the 500 plants: 71 that were 3-lobed, 140 and 71 that produced leaves with extra lobes (i.e., the presence of at least one 4- or 5-lobed leaf) as 141 there was only a single individual in the 5-lobed category; we refer to the 4/5-lobed bulk as the extra 142 lobed bulk. We stored tissue at -80 ℃ prior to DNA extraction and used the Qiagen DNEasy Plant Mini 143 Prep Kit for DNA extraction. We followed the manufacturer’s protocol except for the last step where we 144 used 50µl instead of 100µl of Buffer AE for elution to get a more concentrated final product. Each pool 145 contained equal concentrations of DNA of each individual sample. The Centre for Applied Genomics at 146 SickKids Hospital performed library preparation and paired-end sequencing over two lanes (Illumina 147 NovaSeqX 2x150bp paired-end sequencing). [bioRxiv preprint doi: https://doi.org/10.64898/2026.10.27.762295; this version posted November 2, 2026. The copyright holder for this preprint](https://doi.org/10.64898/2026.10.27.762295) (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made [available under a CC-BY-NC-ND 4.0 International license.](http://creativecommons.org/licenses/by-nc-nd/4.0/) ## 148 Genetic Analysis and Bioinformatics ### 149 Mendelian analysis 150 We first tested whether a simple 1- or 2-locus Mendelian model could explain the distribution of extra 151 lobed leaves. We used a chi-squared test to determine if the phenotypic distribution was significantly 152 different from expectations for a simple Mendelian trait. Based on the presence of extra-lobing in the F 1, 153 we hypothesized that it was the dominant phenotype for a 3:1 expectation, and considered the 4-lobed 154 phenotype as the putative heterozygous phenotype for testing 1:2:1 expectations. We considered 155 testing a two-locus model and 9:3:3:1 expectation, with 3-lobed, 4-lobed, 4/5-lobed and only 5-lobed as 156 the respective categories, but did not because we only observed a single individual in the last category. 157 ### 158 Bioinformatics 159 For genomic data and BSA, unless otherwise indicated, all data was analyzed using high-performance 160 [computers from the Digital Research Alliance of Canada. We decompressed ORA files from SickKids](https://alliancecan.ca/) 161 using Illumina’s ORA decompression software (orad version 2.6.1, Illumina). To assess sequencing 162 quality, we first analyzed the decompressed reads with FastQC (version 0.12.1)(Andrews 2010). Initial 163 trimming was done using Cutadapt (version 5.1) within the Trim Galore wrapper (version 0.6.10), which 164 also automatically ran FastQC for assessing read quality after trimming (Krueger et al. 2023; Martin 165 2011). Reads with a PHRED quality score lower than 20 were removed. We also removed the last 5 bp of 166 all reads to account for an overrepresentation of poly-G tails. Summary statistics for sequencing depth 167 are presented in Table 1. 168 169 We aligned reads to the _I. hederacea_ reference genome (Peake et al. 2026) using _bwa-mem2_ (version 170 2.2.1)(Vasimuddin et al. 2019). We sorted, indexed, and marked duplicates in the resulting bam 171 alignment files using _SAMtools_ (version 1.20)(Danecek et al. 2021). We subsampled reads from the 172 extra-lobed pool to match the sequencing depth of the 3-lobed pool, as discrepancies in read depth can 173 affect downstream tests (Mansfeld and Grumet 2018). We then identified SNPs for each pool using the 174 _HaplotypeCaller_ function from the Genome Analysis Toolkit ( _GATK_, version 4.6.1.0) and then combined 175 the individual SNP files (vcf files) with the CombineGVCFs function (Van der Auwera et al. 2013). We 176 converted this combined SNP matrix into a comma-separated table ( _VariantsToTable_ function) 177 compatible with the _QTLseqR_ pipeline used to perform the BSA in _R_ (version 4.3.3, R Core Team 2024). [bioRxiv preprint doi: https://doi.org/10.64898/2026.10.27.762295; this version posted November 2, 2026. The copyright holder for this preprint](https://doi.org/10.64898/2026.10.27.762295) (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made [available under a CC-BY-NC-ND 4.0 International license.](http://creativecommons.org/licenses/by-nc-nd/4.0/) ### 178 Bulked segregant analysis 179 We used _QTLseqR_ (version 0.7.5.2) to conduct the BSA (Mansfeld and Grumet 2018) which implements 180 both the QTL-seq (Takagi et al. 2013) and the G’ (Magwene et al. 2011) methods. QTL-seq calculates a 181 Δ(SNP-index) over a 10 Mb sliding window (Takagi et al. 2013). The Δ(SNP-index) is the absolute 182 difference in the ratio of reads that differ from the reference genome to the total number of reads at 183 that position between the two bulks. Larger absolute differences in Δ(SNP-index) suggest genes or loci in 184 that region influence the trait and differ between the two bulks, and should approach zero for unlinked 185 loci that are not associated with the phenotype. The original Takagi method averages Δ(SNP-index) 186 across a uniform window, but as suggested by the developers of _QTLseqR_ we use a tricube-smoothed 187 Δ(SNP-index), similar to the G’ method. We calculated 95% and 99% confidence intervals with 188 _QTLseqr_, which randomly assigns alleles to two bulks in the absence of QTL and calculates Δ(SNP 189 index) to establish a null expectation (Mansfeld and Grumet 2018) . We used 10,000 random samples 190 to establish confidence intervals. 191 192 The G’ method calculates a G-statistic for every SNP (Magwene et al. 2011) G’ is then calculated by 193 taking the tricube-weighted average of each SNP’s G-statistic within a 10Mb window to account for 194 variation in sequencing coverage. A higher G’ value indicates greater allele frequency differences 195 between the bulks. An FDR threshold of 0.01 was used as the significance threshold. We report the 196 results for G' in Supplementary Materials, and in the main text we present Δ(SNP-index) results with a 197 focus on cases where the two methods identify the same QTL intervals. ## 198 Gene mapping and GO enrichment analysis 199 We next identified candidate genes contributing to extra-lobing using the _I. hederacea_ genome 200 annotation (Peake et al. 2026) based on the results from the BSA. Loci with tricube-smoothed Δ(SNP 201 index) greater than the 95% confidence interval were selected for further investigation. We used the 202 _map_snp_to_gene()_ function from the _snpsettest_ package (version 0.1.2) with a 20 kb window on either 203 side of each gene (Joo and Himes 2023). We identified _I. hederacea_ genes in the significant QTLs by 204 finding the best-aligning protein-coding genes (lowest e-value, e-value cut-off of 0.001) within the _A._ 205 _thaliana_ genome (Araport 11, Cheng et al. 2017) and _S. lycopersicum_ genome (ITAG 4.0, Hosmani et al. 206 2019). A full list of genes in QTL intervals is presented in Supplementary Table 1 with hypothesized 207 candidate genes presented in the discussion. [bioRxiv preprint doi: https://doi.org/10.64898/2026.10.27.762295; this version posted November 2, 2026. The copyright holder for this preprint](https://doi.org/10.64898/2026.10.27.762295) (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made [available under a CC-BY-NC-ND 4.0 International license.](http://creativecommons.org/licenses/by-nc-nd/4.0/) 208 Additionally, we identified functions significantly enriched in the QTLs-of-interest by conducting a GO 209 enrichment analysis. Genes in _I. hederacea_ inherited GO terms from their best gene detected in _A._ 210 _thaliana_ (i.e., the gene in _A. thaliana_ with the lowest e-value). We conducted a GO enrichment analysis 211 using a Fisher’s exact test ( _topGO_ package, version 2.54.0, Alexa and Rahnenfuhrer 2023) with the 212 weight01 algorithm to account for the hierarchical nature of GO terms. The list of significant GO terms is 213 in Supplemental Materials with those related to plant growth and development highlighted in the 214 results. # 215 Results ## 216 Phenotypes did not conform to simple Mendelian ratios 217 We observed extra-lobing in a common environment where F 2 individuals had been randomized to their 218 locations, suggesting that extra lobing can be observed even in the absence of G*E interactions. We next 219 tested whether extra-lobing followed a simple Mendelian basis. Based on the observed phenotypic 220 distributions, it is likely that extra-lobing in _I. hederacea_ does not follow a simple 1- or 2-locus 221 Mendelian model. Leaf-lobe phenotypes were almost uniformly distributed among offspring: 36.8% had 222 only 3-lobed leaves, 34.6% produced at least some 4-lobed leaves, and 26.2% had 4-lobed leaves with at 223 least one 5-lobed leaf ( 224 Table 2). The distribution of phenotypes differed significantly from the 1:2:1 expectation (ꭓ [2] = 52.83, df = 225 2, P <0.0001) and 3:1 expectation (ꭓ [2] = 42.01, df = 1, P <0.0001) (Figure 2) 226 227 Figure 2: Phenotypic distributions for 1:2:1 and 3:1 Mendelian expectations. Green bars indicate observed 228 frequencies, blue bars indicate expected frequencies. Chi-square tests between the observed and expected values [bioRxiv preprint doi: https://doi.org/10.64898/2026.10.27.762295; this version posted November 2, 2026. The copyright holder for this preprint](https://doi.org/10.64898/2026.10.27.762295) (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made [available under a CC-BY-NC-ND 4.0 International license.](http://creativecommons.org/licenses/by-nc-nd/4.0/) 229 all significantly differed for both the 1:2:1 (χ [2] = 52.83, df =2, P <0.0001) and 3:1 (χ [2] = 42.01, df=1, P <0.0001) 230 expectations. ## 231 BSA identified loci underlying extra-lobed phenotype on two chromosomes 232 We found that there were significant differences between the 3-lobed and extra-lobed bulks associated 233 with leaf shape, suggesting that the propensity for producing extra-lobing is heritable and that QTLs 234 differing between the parental lines may underlie the phenotype. We identified two QTLs that show 235 enrichment for SNPs over-represented in the extra-lobed bulk: one on Chromosome 2 and the other on 236 Chromosome 4 (Table 3, Figure 3, Supplementary Figure 1, Supplementary Figure 2). Peake et al. (2026) 237 recently identified a 117 kb insertion-deletion (indel) polymorphism on Chromosome 2 that perfectly co 238 segregates with entire and 3-lobed genotypes, where entire genotypes lack the 117 kb region. The QTL 239 we detected, in a cross between between lobed genotypes which have the indel region intact, overlaps 240 ~ 52% of the indel region identified by (Peake et al. 2026) (Figure 4). [bioRxiv preprint doi: https://doi.org/10.64898/2026.10.27.762295; this version posted November 2, 2026. The copyright holder for this preprint](https://doi.org/10.64898/2026.10.27.762295) (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made [available under a CC-BY-NC-ND 4.0 International license.](http://creativecommons.org/licenses/by-nc-nd/4.0/) 241 242 Figure 3: Plots showing Δ(SNP indices) across Chromosomes 2 and 4. Red line indicates a 95% confidence interval, 243 blue line indicates 99% confidence interval. Yellow bar indicates significant regions. [bioRxiv preprint doi: https://doi.org/10.64898/2026.10.27.762295; this version posted November 2, 2026. The copyright holder for this preprint](https://doi.org/10.64898/2026.10.27.762295) (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made [available under a CC-BY-NC-ND 4.0 International license.](http://creativecommons.org/licenses/by-nc-nd/4.0/) 244 245 Figure 4 : Zoom in on Chromosome 2, showing the QTL region identified in the BSA (yellow) next to the 246 most significant SNPS in a GWAS for 3-lobed versus entire leaves (dotted lines) and the coordinates for 247 the indel (light blue region), identified by (Peake et al. 2026). The green shaded interval indicates the 248 overlap between the indel identified by Peake et al. and the QTL region identified here. Red line 249 indicates a 95% confidence interval, blue line indicates 99% confidence interval. ## 250 QTLs contain genes involved in leaf growth and development 251 We found 98 gene IDs in the QTLs (Table 4, Supplementary Table 1). On Chromosome 2, we detected 252 multiple genes involved in auxin distribution and response, as well as genes related to leaf polarity, cell 253 expansion, sucrose synthase, and epidermal development, some of which also indirectly relate to auxin 254 distribution and proper PIN protein expression (Table 5). These genes are _PIN-LIKES 1 (PILS1), AUXIN_ 255 _RESPONSE FACTOR 8 (ARF8), KANADI 1 (KAN1), EPIDERMAL PATTERNING FACTOR-LIKE 1 (EPFL1),_ 256 _EXPANSIN 13 (EXPA13), NAC28_ [named after _**N**_ _O APICAL MERISTEM_ ( _NAM_ ), _**A**_ _RABIDOPSIS_ 257 _TRANSCRIPTION ACTIVATOR FACTOR_ 1/2 ( _ATAF1/2_ ), and _**C**_ _UP-SHAPED COTYLEDON 2_ ( _CUC2_ )] _,_ multiple 258 _SUCROSE SYNTHASE (SUS)_ genes _, HOMEODOMAIN GLABROUS 11 (HDG11),_ and _ZWICHEL_ ( _ZWI)_ . The QTL [bioRxiv preprint doi: https://doi.org/10.64898/2026.10.27.762295; this version posted November 2, 2026. The copyright holder for this preprint](https://doi.org/10.64898/2026.10.27.762295) (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made [available under a CC-BY-NC-ND 4.0 International license.](http://creativecommons.org/licenses/by-nc-nd/4.0/) 259 on Chromosome 4 contained a gene involved in regulating organ size, _BIG BROTHER (BB)_, and another 260 involved in activating a KNOX gene, _NO TRANSMITTING TRACT (NTT_ ) (Table 5). Only 5 SNPs fell within 261 the coordinates of any genes in the QTLs, one of which was a potential gene of interest: _HDG11_ . We 262 detail the specifics of the leaf development-related genes of interest in the Discussion. ## 263 GO enrichment analysis 264 We found 77 significant biological process GO terms and 40 significant molecular function GO terms. We 265 report all of these in Supplementary Table 2 and Supplementary Table 3 for completeness. Here in the 266 main text, we report the top 7 biological process and top 3 molecular function GO terms, which have the 267 strongest P values (P < 0.00009) and approximately the top 9% and 7.5% of GO terms respectively, in 268 addition to the GO terms described above with leaf shape candidate genes. 269 270 The top 7 biological process GO terms are related to nuclear-transcribed mRNA catabolic process, 271 nonsense-mediated decay (GO:0000184), long-day photoperiodism (GO:0048571), RNAi-mediated 272 antiviral immune response (GO:0009616), pollen-pistil interaction (GO:0009875), priming of cellular 273 response to stress (GO:0080136), positive regulation of defense response (GO:1900426), and RNA 274 splicing (GO:0008380). The top 3 molecular function GO terms are 5'-3' DNA helicase activity 275 (GO:0043139), RNA helicase activity (GO:0003724), and myosin binding (GO:0017022). In all of these 276 cases, it is difficult to discern a relationship between the GO terms and leaf shape and morphology. # 277 Discussion 278 We identified multiple QTLs associated with extra-lobing in ivyleaf morning glory, suggesting that there 279 is a genetic influence to the propensity of producing extra lobed leaves. Establishing that there is a 280 genetic basis underlying the propensity to produce extra-lobed leaves is a necessary first step prior to 281 future studies of its microevolutionary or ecological significance (Conner and Hartl 2004). In contrast to 282 the well-studied entire -vs- 3-lobed polymorphism in this species, the propensity for producing extra 283 lobed leaves did not follow Mendelian segregation patterns. Our BSA results suggest that multiple loci 284 may be involved in the propensity for producing extra lobes, including a QTL that maps to the same 285 region as the entire -vs- 3-lobed polymorphism, suggesting that gene(s) in this region underlie leaf 286 shape, morphology, and development in _I. hederacea_ . Below, we discuss in detail some of the candidate 287 genes present in these QTL intervals and future directions. [bioRxiv preprint doi: https://doi.org/10.64898/2026.10.27.762295; this version posted November 2, 2026. The copyright holder for this preprint](https://doi.org/10.64898/2026.10.27.762295) (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made [available under a CC-BY-NC-ND 4.0 International license.](http://creativecommons.org/licenses/by-nc-nd/4.0/) ## 288 Chromosome 2 Candidate Genes 289 We found multiple genes in the QTL on Chromosome 2 that are involved in auxin transport and auxin 290 inducible responses. The first is _PIN-LIKES 1_ ( _PILS1_ ) gene (GO:0080162, p = 0.005). _PILS_ encodes for 291 proteins that are hypothesized to have similar functions to PIN proteins in that they facilitate auxin 292 transport and cellular response to auxin (Barbez et al. 2012; Sauer and Kleine-Vehn 2019). A second 293 auxin-related gene in this QTL interval is _AUXIN RESPONSE FACTOR 8_ ( _ARF8_ ). _ARFs_ are transcription 294 factors that regulate auxin response genes and are involved in many aspects of plant growth and 295 development (Li et al. 2016). Many _ARFs_ work redundantly and share structural similarity (Okushima et 296 al. 2005). _ARF8_ specifically promotes proximal-distal leaf growth, and also represses Class-1 _KNOX_ genes 297 in floral organs, causing abnormal petal and vasculature development, and somewhat uneven leaf 298 development upon floral initiation (Tabata et al. 2010; Y. Xiong et al. 2021). In tomato, _SlARF8_ was also 299 found to play a role in determining leaf morphology (Wu et al. 2018). A third gene, _KANADI_ _1_ ( _KAN1_ ), 300 was also present in the QTL, and it specifies the development of the abaxial leaf identity (GO:0010158, p 301 = 0.002)(Emery et al. 2003; Eshed et al. 2004; Kerstetter et al. 2001; Pekker et al. 2005). _KANADI_ genes 302 also influence the distribution of auxin within the developing embryo, regulates PIN expression, and 303 vascular tissue development (Burian et al. 2022; Emery et al. 2003; Eshed et al. 2004; Guan et al. 2017; 304 Ilegems et al. 2010; Izhaki and Bowman 2007). ARF3 and ARF4 also work in cooperation with _KANADI_ 305 genes to specify abaxial cell types (Pekker et al. 2005). Failure of either adaxial or abaxial identities to 306 develop results in a lack of proper lamina outgrowth. For example, ectopic expression of _KANADI_ genes 307 in leaf primordia restricts marginal, and therefore lobe, outgrowth (Eshed et al. 2004). In Japanese 308 morning glory ( _Ipomoea nil_ ), mutations in _KAN1_, along with potentially other modifiers, cause improper 309 establishment of the abaxial identity in lateral organs, leading to curled leaves and separated petals 310 (Iwasaki and Nitasaka 2006). Lastly, _EPIDERMAL PATTERNING FACTOR-LIKE 1_ ( _EPFL1)_ is involved in 311 regulating shoot development, stomatal patterning, shoot apical meristem size, leaf initiation, and organ 312 elongation (Bessho-Uehara et al. 2016; Bundy et al. 2012; Hara et al. 2007; Kosentka et al. 2019; 313 Shimada et al. 2011). EPFL1 and 2 were both found to be necessary for the formation of sharp auxin 314 maxima in developing leaves and the shoot apical meristem, as _epfl1_ mutants have shallower leaf 315 serrations, and _epfl1 epfl2_ double mutants have broader auxin maxima (Tameshige et al. 2025). 316 Collectively, _EPFL1_, _KAN1_, _ARF8_, and _PILS1_ represent promising candidate genes for variation in leaf 317 morphology. 318 There are four other genes of interest present within the QTL on Chromosome 2 that may be related to 319 leaf growth; for these genes, they belong to gene families that have members that have been [bioRxiv preprint doi: https://doi.org/10.64898/2026.10.27.762295; this version posted November 2, 2026. The copyright holder for this preprint](https://doi.org/10.64898/2026.10.27.762295) (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made [available under a CC-BY-NC-ND 4.0 International license.](http://creativecommons.org/licenses/by-nc-nd/4.0/) 320 demonstrated to be involved in leaf growth, development, or shape. We include these genes as 321 candidates because _I. hederacea_ is a non-model organism, and the genetic basis of leaf shape is often 322 lineage specific (Nicotra, 2011). The first is _EXPANSIN A13_ ( _EXPA13_ ) for _A. thaliana_, or expansin 323 precursor 3 in tomato. Expansins ( _EXP_ ) belong to a large gene family with diverse and tissue-specific 324 roles but are known to be involved with cell wall loosening (Cosgrove 2024). They are involved in leaf 325 growth, as induced local expression of expansin in leaves causes outgrowths to develop (Pien et al. 326 2001). Again, auxin plays a part here: auxin reduces the pH of plant cells, and this acidic environment is 327 required for expansin activity to occur (Cosgrove 2024). The second is _NAC28_ or _NAC53_ transcription 328 factor in _A. thaliana_ and tomato, respectively. NAC is a very large family of transcription factors. They 329 are involved in diverse processes including embryogenesis, cotyledon development, biotic and abiotic 330 stress responses, and lateral organ development (H. Xiong et al. 2025). This family contains a well 331 known player in leaf lobing formation, _CUC2_, which promotes leaf serrations in simple-leaved species 332 like _A. thaliana_ or more leaf dissections in compound species like tomato (Berger et al. 2009; Blein et al. 333 2008; Hasson et al. 2011). _NAC028_ was found to be upregulated in more complex leaves of the 334 heteroblastic species _Gevuina avellana_ (Ostria-Gallardo et al. 2016; Wen et al. 2022). _NAC53_ also 335 encodes _ALADIN_, a protein involved in proper cell division, stem elongation, and plant development 336 (Best et al. 2021). Third, we detected multiple _SUCROSE SYNTHASE (SUS)_ genes, which may be involved 337 in leaf development and auxin signalling, as tomatoes with _SlSUS1_, _SlSUS3_ and _SlSUS4_ mutations 338 displayed deformed leaves and elevated _PIN1_ levels (Goren et al. 2017). Fourth, this QTL interval 339 contained _HOMEODOMAIN GLABROUS 11_ ( _HDG11_ ) for _A. thaliana,_ or HD-zip protein ROC8 in tomato, 340 which belongs to the Class IV HD-Zip family. _HDG11_ was the only leaf development-related gene 341 containing a SNP. The Class IV HD-Zip family is involved with the differentiation of specialized epidermal 342 cells such as guard cells, pavement cells, and trichomes (Schrick et al. 2023). In Chinese kale, mutants 343 that overexpressed _HDG11_ had higher _YUCCA_, _EXPANSIN_, and _PIN_ expression (Zhu et al. 2016). 344 ## 345 Chromosome 4 Candidate Genes 346 The majority of the genes on the QTL on Chromosome 4 do not have obvious relationships with leaf 347 shape. However, there are two of note. _BIG BROTHER_ ( _BB_ ) encodes a RING finger protein and is a 348 negative regulator of plant organ size by restricting the duration of cellular proliferation (Disch et al. 349 2006). Mutants experience increased leaf growth and a delayed transition from cellular proliferation to 350 differentiation, and overexpression leads to significantly smaller leaf area (Vanhaeren et al. 2017). _NO_ 351 _TRANSMITTING TRACT_ ( _NTT_ ) is a zinc finger transcription that activates a Class 1 _KNOTTED-LIKE_ [bioRxiv preprint doi: https://doi.org/10.64898/2026.10.27.762295; this version posted November 2, 2026. The copyright holder for this preprint](https://doi.org/10.64898/2026.10.27.762295) (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made [available under a CC-BY-NC-ND 4.0 International license.](http://creativecommons.org/licenses/by-nc-nd/4.0/) 352 _HOMEOBOX_ ( _KNOX_ ) gene, _BREVIPEDICELLUS_ ( _BP/KNAT1_ ). _NTT_ has been studied more so for its role on 353 fruit development, but overexpression or ectopic expression also causes irregular leaf margins and 354 shorter internodes, similarly to when _BP/KNAT1_ is overexpressed (Chuck et al. 1996; Chung et al. 2013; 355 Lincoln et al. 1994; Marsch-Martínez et al. 2014). 356 # 357 Conclusions and Future Directions 358 Nearly a century ago, classical work in _Ipomoea nil_ (L.) Roth, the sister species to _I. hederacea_, 359 attempted to discern the genetic basis of mutant four or five lobed phenotypes, observed in contrast to 360 the typical 3-lobed phenotype (Imai 1938). The distribution of phenotypes observed by Imai (1938) also 361 failed to conform to patterns of Mendelian segregation, and he hypothesized that modifier or 362 suppressor genes were involved in this phenotype. Our results from _I. hederacea_ also fail to detect a 363 simple genetic basis for this phenotype and our BSA results suggest that multiple chromosomal regions 364 may underlie this propensity. 365 366 While our work suggests that this phenotype does have a genetic influence, the ecological and 367 evolutionary consequences of this shape variation– if any– remain unclear. Whether extra-lobing– either 368 its presence or the number of extra-lobed leaves produced– confers differences in ecophysiology, 369 geographic distribution, ecology, and fitness like the 3-lobed and entire phenotypes (Boyle et al. 2024; 370 Bright and Rausher 2008; Bright-Emlen 1998; Campitelli et al. 2008, 2013; Campitelli and Stinchcombe 371 2013, 2014; Elmore 1986; Ennos 1981; Singhal et al. 2025; Stinchcombe 2002; Stinchcombe et al. 2001) 372 warrants future investigation. 373 # Acknowledgements 374 We thank members of the Stinchcombe Lab for discussion and encouragement, Jannice Friedman for 375 advice on BSA, and Tom Gludovacz and Alice DesRoches for horticultural support. We thank Jacqueline 376 Sztepanacz, Asher Cutter, and Megan Bontrager for comments on previous versions of the manuscript. 377 # Data Availability Statement 378 The raw sequence reads supporting the findings of this study have been deposited in the NCBI SRA 379 under BioProject PRJNA1346405. These data will be publicly released upon publication. All code can be 380 found on [GitHub.](https://github.com/marthenry/ipomoea_hederacea_bsa_2026/) [bioRxiv preprint doi: https://doi.org/10.64898/2026.10.27.762295; this version posted November 2, 2026. The copyright holder for this preprint](https://doi.org/10.64898/2026.10.27.762295) (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made [available under a CC-BY-NC-ND 4.0 International license.](http://creativecommons.org/licenses/by-nc-nd/4.0/) 381 # Study Funding 382 NSERC Canada, University of Toronto Department of Ecology and Evolutionary Biology. # 383 Tables 384 Table 1: Summary of Illumina NovaSeqX sequencing data. **Sample** **3-lobed** **Extra-lobed** Number of mapped reads 320,399,224 (99.87%) 364,285,564 (99.87%) Mean depth 66.0866x 75.1754x Coverage standard deviation 275.6161 312.033x Coverage >= 1x (%) 99.4 99.46 Coverage >= 5x (%) 98.8 98.92 Coverage >= 10x (%) 98.25 98.45 Coverage >= 40x (%) 89.58 92.76 385 386 Table 2: Total leaf-shape phenotypes. Plants were scored as either 3-lobed, 4-lobed if they had at least one leaf 387 with an extra lobe, 4- and 5-lobed if they had at least one of each, and 5-lobed if they had at least one leaf with 5388 lobes. **Phenotype:** **3-lobed** **4-lobed** **4- and 5- lobed** **5-lobed** Number of plants 184 173 131 1 Percentage 36.8% 34.6% 26.2% 0.2% 389 390 Table 3: QTLs identified from bulked segregant analysis using the Δ(SNP index) calculated from the QTLseq 391 method. CI = 95%. **posPeak** **DeltaSNP** **avgDelta** **SNP** **avgSNPs_** **Chr** **QTL** **start** **end** **length** **nSNPs** **Mb** **peakDelta** **SNP** 0.26618152 0.26076528 Chr2 1 3681062 5333261 1652199 549 332 4594636 6360833 3780902 0.24766151 0.22694150 Chr4 2 14392492 15251903 859411 939 1093 14822530 0174778 7332453 392 393 Table 4: Number of gene IDs in the QTLs on Chromosomes 2 and 4, as well as how many mapped to _Arabidopsis_ 394 _thaliana_ and _Solanum lycopersicum_ genes. **Number of** _**I. hederacea**_ **gene IDs** **Number of** _**A. thaliana**_ **genes** **Number of** _**S. lycopersium**_ **genes** Chr2 63 68 76 Chr4 35 34 37 Total 98 102 113 395 [bioRxiv preprint doi: https://doi.org/10.64898/2026.10.27.762295; this version posted November 2, 2026. The copyright holder for this preprint](https://doi.org/10.64898/2026.10.27.762295) (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made [available under a CC-BY-NC-ND 4.0 International license.](http://creativecommons.org/licenses/by-nc-nd/4.0/) 396 Table 5: List of hypothesized candidate genes, due to their known roles in leaf growth and development. **Arabidopsis thaliana gene** **Solanum** **lycopersicum** **accession ID** **Solanum lycopersicum gene** **Ipomoea** **hederacea** **gene ID** **Chr** **Arabidopsis** **thaliana** **accession ID** g17376 Chr2 AT1G65910 NAC 28 Solyc02g081270 NAC domain-containing protein 53 (AHRD V3.3 *** A0A2G2XFS7_CAPBA) g17378 Chr2 AT3G03220 EXPANSIN 13 Solyc03g031840 expansin precursor 3 g17379 Chr2 AT1G73360 HOMEODOMAIN Solyc11g011940 homeobox-leucine zipper protein ROC8 GLABROUS 11 (AHRD V3.3 *** A0A2I4EBE3 9ROSI) Solyc11g011940 homeobox-leucine zipper protein ROC8 GLABROUS 11 (AHRD V3.3 *** A0A2I4EBE3_9ROSI) g17384 Chr2 AT5G16560 KANADI 1 (KAN1) Solyc11g011770 Homeodomain-like superfamily protein (AHRD V3.3 *-* A0A2U1PJR7_ARTAN) g17385 Chr2 AT4G02280 SUCROSE SYNTHASE 3 Solyc02g081300 Sucrose synthase (AHRD V3.3 *** K4BA00_SOLLC) g17385 Chr2 AT4G02280 SUCROSE SYNTHASE 3 Solyc03g098290 Sucrose synthase (AHRD V3.3 *** K4BJP4_SOLLC) g17385 Chr2 AT4G02280 SUCROSE SYNTHASE 3 Solyc09g098590 Sucrose synthase (AHRD V3.3 *** E0Z1D1_SOLLC) g17385 Chr2 AT5G37180 SUCROSE SYNTHASE 5 Solyc09g098590 Sucrose synthase (AHRD V3.3 *** E0Z1D1_SOLLC) g17385 Chr2 AT5G37180 SUCROSE SYNTHASE 5 Solyc02g081300 Sucrose synthase (AHRD V3.3 *** K4BA00_SOLLC) g17385 Chr2 AT5G37180 SUCROSE SYNTHASE 5 Solyc03g098290 Sucrose synthase (AHRD V3.3 *** K4BJP4_SOLLC) g17385 Chr2 AT1G73370 SUCROSE SYNTHASE 6 Solyc03g098290 Sucrose synthase (AHRD V3.3 *** K4BJP4_SOLLC) g17385 Chr2 AT1G73370 SUCROSE SYNTHASE 6 Solyc02g081300 Sucrose synthase (AHRD V3.3 *** K4BA00_SOLLC) g17385 Chr2 AT1G73370 SUCROSE SYNTHASE 6 Solyc09g098590 Sucrose synthase (AHRD V3.3 *** E0Z1D1_SOLLC) g17412 Chr2 AT5G37020 AUXIN RESPONSE FACTOR Solyc03g031970 Auxin response factor (AHRD V3.3 *** 8 E0A8P3_SOLLC) g17412 Chr2 AT5G37020 AUXIN RESPONSE FACTOR Solyc02g037530 Auxin response factor 8B 8 g17413 Chr2 AT5G65930 ZWICHEL Solyc02g068340 Kinesin-like protein (AHRD V3.3 *** O24147_TOBAC) g17419 Chr2 AT1G20925 PIN-LIKES 1 Solyc04g082830 Auxin efflux carrier (AHRD V3.3 *** A0A200PR79_9MAGN) g17420 Chr2 AT1G20925 PIN-LIKES 1 Solyc02g037550 Auxin efflux carrier (AHRD V3.3 *** A0A2U1MR93_ARTAN) g17446 Chr2 AT5G10310 EPIDERMAL PATTERNING FACTOR-LIKE 1 Solyc11g009040 EPIDERMAL PATTERNING FACTOR-like FACTOR-LIKE 1 protein 1 (AHRD V3.3 *** A0A2G2WTE5_CAPBA),Pfam:PF17181 g23362 Chr4 AT3G63530 BIG BROTHER Solyc01g087060 RING/U-box superfamily protein (AHRD V3.3 *** A0A2U1NQN4_ARTAN) g23364 Chr4 AT3G57670 NO TRANSMITTING TRACT Solyc01g087050 Zinc finger protein (AHRD V3.3 *** A0A200QA40_9MAGN) 397 [bioRxiv preprint doi: https://doi.org/10.64898/2026.10.27.762295; this version posted November 2, 2026. 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