Science, Faculty of
DSpace
UBCV
Lande, Kathryn
Master of Science - MSc
University of British Columbia
Recent analyses of the genomes of three wild sunflower species (Helianthus annuus, H. petiolaris, H. argophyllus) have uncovered 37 non-recombining, highly divergent haploblocks, all of which are megabases long. The lack of recombination between alternate haplotypes of these regions has been shown to result from segregating chromosomal structural variants (SVs) in many cases. These SVs are distributed along environmental clines. Genome-Wide Association Studies (GWAS) and Genome-Environment Association (GEA) analyses indicate that the SVs are strongly associated with certain climate and soil conditions, as well as a wide range of phenotypic traits and ecotypes. They are also significant from an evolutionary standpoint by providing a potential explanation for how these species are able to maintain a wide variety of locally adapted ecotypes and ecospecies despite considerable gene flow between distinct populations. However, while substantial high-level work has been done to identify the phenotypic traits, habitat associations, and phylogenetic origins of these SVs, there had been little characterization of the genes housed within the SVs before now. Through the subsequent analyses, I characterize the haplotype-specific genetic and transcriptomic divergence between gene variants using a mix of genomic and transcriptomic data sets previously generated by the Rieseberg Lab and collaborators. In so doing, I find that alternate haplotypes of these SVs demonstrate remarkable divergence in genes potentially related to local adaptation and the functions predicted in previous studies. I also investigate the evolutionary forces acting on each SV to show that both haplotype-specific positive and negative selection appear abundant. Finally, through population genetics I provide evidence that these SVs had introgressive origins.
Genomic Characterization of DivergentHaplotypes of Large Structural Variants in theGenus HelianthusbyKathryn LandeB.Sc, McGill University, 2018A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THEREQUIREMENTS FOR THE DEGREE OFMASTER OF SCIENCEinThe Faculty of Graduate and Postdoctoral Studies(Genome Science and Technology)THE UNIVERSITY OF BRITISH COLUMBIA(Vancouver)April 2021© Kathryn Lande, 2021The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the thesis entitled: Genomic Characterization of Divergent Haplotypes of Large Structural Variants in the Genus Helianthus submitted by Kathryn Lande in partial fulfillment of the requirements for the degree of Master of Science in Genome Science and Technology Examining Committee: Dr. Loren Rieseberg, Department of Botany Supervisor Dr. Judith Mank, Department of Zoology Supervisory Committee Member Dr. Joerg Bohlmann, Department of Forestry Supervisory Committee Member Dr. Peter Stirling, Department of Medical Genetics Additional Examiner Additional Supervisory Committee Members: Supervisory Committee Member Supervisory Committee Member ii, UBC, UBC, UBC, UBCAbstractRecent analyses of the genomes of three wild sunflower species (Helianthus annuus, H.petiolaris, H. argophyllus) have uncovered 37 non-recombining, highly divergenthaploblocks, all of which are megabases long. The lack of recombination betweenalternate haplotypes of these regions has been shown to result from segregatingchromosomal structural variants (SVs) in many cases.These SVs are distributed along environmental clines. Genome-Wide AssociationStudies (GWAS) and Genome-Environment Association (GEA) analyses indicate that theSVs are strongly associated with certain climate and soil conditions, as well as a widerange of phenotypic traits and ecotypes. They are also significant from an evolutionarystandpoint by providing a potential explanation for how these species are able tomaintain a wide variety of locally adapted ecotypes and ecospecies despite considerablegene flow between distinct populations. However, while substantial high-level work hasbeen done to identify the phenotypic traits, habitat associations, and phylogeneticorigins of these SVs, there had been little characterization of the genes housed within theSVs before now.Through the subsequent analyses, I characterize the haplotype-specific genetic andtranscriptomic divergence between gene variants using a mix of genomic andtranscriptomic data sets previously generated by the Rieseberg Lab and collaborators. Inso doing, I find that alternate haplotypes of these SVs demonstrate remarkabledivergence in genes potentially related to local adaptation and the functions predicted inprevious studies. I also investigate the evolutionary forces acting on each SV to showthat both haplotype-specific positive and negative selection appear abundant. Finally,through population genetics I provide evidence that these SVs had introgressive origins.iiiLay SummaryThe key aim of this research was to identify the genetic differences that allow wildsunflowers populations to adapt to a wide variety of environments and stresses.Specifically, I investigate areas of the genome which vary in structure, such as in thepresence or order of genes. These regions – referred to as structural variants – are knownto be highly divergent between populations optimized for different environments orlifestyles. My characterization of the variation between structural variant states querieddifferences of many kinds, including those of: gene sequence, the extent to which genesare expressed, and the evolutionary forces acting on the genes. Additionally, I describethe genetic composition of alternate states of these regions, and find evidence that theyhave unique population sizes and origins. These results add to our understanding ofsunflower evolution and speciation, and provide a jumping-off point for future researchinto these genomic regionsivPrefaceThe results of this thesis are the original, unpublished, work by the author, K.Lande. All analyses contained herein are the independent work of the author, barringthe HKA test which was performed by Dr. Kaichi Huang.All raw data used in this thesis were originally produced by other authors.Samples used for Chapter 2 were sequenced by M. Todesco et al. (2020) of which I am anauthor, and samples used for Chapter 3 were originally produced by Lee et al. (2021).Expression libraries were additionally sourced from H. Badouin et al. (2017). Singlenucleotide polymorphism (SNP) data was extracted from the M. Todesco et al (2020)data by Dr. Kaichi Huang.vTable of ContentsAbstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iiiLay Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ivPreface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vTable of Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viList of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ixList of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xAcknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiDedication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xii1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11.1 Introduction to Structural Variation . . . . . . . . . . . . . . . . . . . . . . . . 11.2 Roles of SVs in Helianthus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 Genomic Characterization of Diverging Haploblocks . . . . . . . . . . . . . . . 42.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42.2 Materials and Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52.2.1 Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52.2.2 Reference Annotations . . . . . . . . . . . . . . . . . . . . . . . . . . . 52.2.3 Expression Enrichment Tests . . . . . . . . . . . . . . . . . . . . . . . 62.2.4 Ha412 Gene Ontology . . . . . . . . . . . . . . . . . . . . . . . . . . . 62.2.5 TAIR Homolog Enrichment Scans . . . . . . . . . . . . . . . . . . . . 72.2.6 dN/dS Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72.2.7 HKA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8vi2.2.8 Diversity Calculations . . . . . . . . . . . . . . . . . . . . . . . . . . . 82.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92.3.1 Functional Enrichments Within Haploblocks . . . . . . . . . . . . . . 92.3.2 Haplotype-specific Genetic Alterations . . . . . . . . . . . . . . . . . 112.3.3 Population Genetics of Divergent Haplotypes . . . . . . . . . . . . . . 182.3.4 Evolutionary Forces Acting on Haplotype-Specific Gene Variants . . 202.4 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 272.4.1 Functional Clustering Inside Helianthus Haploblocks . . . . . . . . . 272.4.2 Sequence Divergence between SV Haplotypes . . . . . . . . . . . . . 282.4.3 Population Genetics of SV Haplotypes . . . . . . . . . . . . . . . . . . 302.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333 Transcriptomic Characterization of Two H. Annuus Haploblocks . . . . . . . . . 343.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 343.2 Materials and Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 363.2.1 Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 363.2.2 Transcriptome Alignment . . . . . . . . . . . . . . . . . . . . . . . . . 363.2.3 Differential Gene Expression . . . . . . . . . . . . . . . . . . . . . . . 363.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373.3.1 Patterns of Differentially Expressed Genes . . . . . . . . . . . . . . . 373.3.2 Lignin Content by Ann.05.01 Haplotype . . . . . . . . . . . . . . . . . 403.4 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 423.4.1 Haplotype-Specific Transcriptomic Differences . . . . . . . . . . . . . 423.4.2 HCT and Lignin Biosynthesis in Chr05 Haploblocks . . . . . . . . . . 423.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 444 Concluding Chapter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47viiAppendices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54Appendix A: Supplementary Methods . . . . . . . . . . . . . . . . . . . . . . . . . 54Appendix B: Supplementary Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . 57Appendix C: Supplementary Figures . . . . . . . . . . . . . . . . . . . . . . . . . . 60viiiList of Tables2.1 Total Number of Homologous Gene Clusters Inside Helianthus ssp Hap-loblocks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102.2 Predicted Protein Products with the Largest Grantham Distance betweenHaplotypes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122.3 GO Terms with the Largest Grantham Distances in Haploblocks Comparedto the Genomic Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162.4 Silent Mutation Fixation Rates between Haploblocks . . . . . . . . . . . . . . 182.5 Pi Diversity versus Fixed Silent Mutation Frequency between HaploblockHaplotypes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192.6 Watterson’s Theta and Effective Population Size Estimates for Haploblocks 202.7 Significant Mcdonald-Krietman Test Genes . . . . . . . . . . . . . . . . . . . 232.8 Significant HKA genes by SV Haplotype with GO Terms . . . . . . . . . . . 242.9 Top Candidate Genes for Selective Sweep in Each Haploblock . . . . . . . . 263.1 Single and Multi-mapping DEG overlap between SAM208 and SAM004 . . 373.2 DEG Enrichment within Haploblocks by Age and Tissue . . . . . . . . . . . 383.3 Highly Homologous Gene Clusters in Ann.05.01 . . . . . . . . . . . . . . . . 403.4 Contributions to HCT Expression by Tissue . . . . . . . . . . . . . . . . . . . 40ixList of Figures2.1 Enrichment of the 25Most Divergent GO Terms as a Function of Percentageof Total Grantham Distance for each Haploblock . . . . . . . . . . . . . . . . 142.2 Plot of dN/dS of Fixed Sites vs. p-Value for all Haplotype-specific GeneVariants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213.1 Top 10 GO Terms by Total Grantham Distance Between Haplotype-specificGene Variants in Ha412HOChr05 Haploblocks . . . . . . . . . . . . . . . . . 41xAcknowledgementsI am extremely grateful to my supervisor Loren Rieseberg for the years of supportand mentorship he has given me during my time at the University of British Columbia. Iam also eternally appreciative for the help and friendship of the rest of the Lab,specifically, Kaichi Huang and Joon Lee for their direct contributions to the researchcontained within this thesis. I would also like to thank Jean-Sebastien Legare forspending two months helping me call SNPs for an analysis that ended up beinginconclusive, Winnie Cheung for being the best lab manager ever, and the many otherswhose data and advice have donated to the findings of this thesis.I would also like to thank my committee members, Dr. Judith Mank and Dr. JoergBohlmann, for their knowledge and guidance, as well as the University of BritishColumbia and NSERC for their financial support.Lastly, I’d like to thank my friends Samantha Bovaird and Graeme Keais for theirthoughtful responses to my manic, late-night messages about research results.xiDedicationTo J.W. My star, my perfect silence.xiiChapter 1Introduction1.1 Introduction to Structural VariationStructural variation (SV) refers to any alteration to the genome larger than 1kb.They can include changes in chromosome length (insertions, deletions, or duplications),orientation (inversions), or chromosomal location (translocations)[55]. There are twobroad classes of SVs: balanced and unbalanced. In balanced SVs such as inversions andtranslocations, alternate haplotypes have the same amount of genetic material.Alternatively, haplotypes of unbalanced SVs – such as copy number variations (CNVs) –have differing amounts of genetic material[13]. SVs are generally difficult to detect withtraditional DNA sequencing due to our reliance on reference genomes, and the highlyrepetitive sequences that often flank SV boundaries. Consequently, the presence andimpact of SVs is understudied. Despite this, a great deal of SVs have been identified inplant genomes. Unbalanced SVs have been identified in a variety of species, includingArabidopsis [57], barley[38], foxtail millet[17], maize[46], and soybeans[34]. On the other hand,balanced SVs are known in monkeyflower[11], Arabidopsis [32], cucumber[31], cotton[65],and many others[22] [52] [64] [27].While both types of SV are expected to have large impacts on phenotype, thepresent research focuses on balanced SVs, specifically inversions. Chromosomal1rearrangements have been known for a long time to differentiate species andecotypes[27]. Inversions specifically suppress recombination between oppositehaplotypes, maintaining genetic linkage between favourable allele combinations[36] [11].Moreover, this contributes to speciation by allowing interbreeding populations to adaptto differential environments even in the presence of gene flow[2]. Further, someinversions may even disrupt meiosis in hybrids, causing hybrid sterility[47]. Inversionshave been shown to drive ecotypic differentiation in seaweed flies[41] and rainbowtrout[42], and reproductive isolation in yellow monkeyflower[11].1.2 Roles of SVs in HelianthusHelianthus is a highly diverse genus comprising 49 unique species which can befound in a wide swath of environments[29]. Even within species, wild populations boasta variety of locally adapted ecotypes, and can grow despite a variety of stressors fromdrought[44] to extreme temperatures to flooding[48] [59].The presence of structural variation in Helianthus has been known for a long time.It was first noted by Charles Heisner in 1947 that hybrids of H. annuus and H. petiolarisshowed patterns of abnormal meiosis in cytology experiments, suggesting the existenceof inversions and translocations in the two species[19]. Linkage mapping experimentsconducted decades later confirmed these hypotheses[8]. SV was additionally known toact as a barrier to introgression in Helianthus [33]. Still, the specific genetic andevolutionary functions of these SVs were unclear.However, recent work by Todesco et al 2020[40] and Huang et al 2020[21] suggeststhat many Helianthus ecotypes and complex multigenic phenotypes may be controlledby highly linked genes contained within SVs. Genomic areas of high linkagedisequilibrium in Helianthus species are not only distributed along geographic clines thatwould necessitate alternative adaptation, but they also show strong GEA and GWAsignals for traits and environments associated with those clines[40].2For example, SVs in H. petiolaris ssp. fallax on chromosomes 9, 11, and 14 appear togenerate divergence between dune adapted and non-dune adapted individuals bycontrolling seed morphology. In addition, individuals with alternate haplotypes of astructural variant on H. argophyllus chromosome 6 display a 77-day difference inflowering time owing to a haplotype-specific deletion of an HaFT gene. Moreover,alternate haplotypes of these SVs are associated with a variety of environmental clinesrelating to soil content, temperature, and precipitation, and display strong GWAassociation with phenotypes ranging from flowering time, to plant height, to leaf andseed morphology[40].In this thesis, I will investigate the unexplored genomic variation withinhaplotypes of these newly identified SVs. In my first chapter, I will find the pairwisedifferences, nucleotide diversity, and selective forces acting on haplotype-specific genevariants in order to identify specific genetic differences between SV haplotypes. In mysecond chapter, I will focus specifically on differential gene expression between alternatehaplotypes of two SVs found in domestic H. annuus lines.3Chapter 2Genomic Characterization of DivergingHaploblocks2.1 IntroductionRecent papers have done a great deal to categorize the broad-scale phenotypic andenvironmental trends associated with Helianthus SVs. However, two glaring questionspertaining to the genomic sequences of these regions remain outstanding. Namely, whatspecific genetic differences produce these divergent ecotypes, and what evolutionaryforces are creating them?While we expect that genes related to local adaptation will be divergent betweenhaplotypes, understanding the population genetics of the SVs and the evolutionaryforces acting within them promises to provide greater insight into the origins and rolesof these genomic regions.To investigate these questions, I selected 12 SVs with strong experimental evidencefor divergent local adaptation (Supplementary Table 1). I then identified the genecontent of each haploblock, and found the fixed genetic differences between haplotypesto assess the most likely genetic basis of each haplotype-specific phenotype. Further, Iproduced a database of all SNP divergence between SV haplotypes for future studies.4Finally, I gathered population genetic data of individual SV haplotypes in an attempt touncover their origins and evolutionary history.2.2 Materials and Methods2.2.1 DataSequences of 1,450 wild Helianthus individuals (720 H. annuus individuals, 299 wildH. argophyllus individuals, 259 H. petiolaris ssp. fallax individuals, 168 H. petiolaris ssp.petiolaris individuals, and one individual each of the perennial species H. decapetalus, H.divaricatus, H. giganteus, and H. grosseserratus), GWAS data for 87 phenotypes, and GEAresults for 39 variables come from Todesco et al 2020[40]. SNPs for these samples wereextracted from VCFs aligned directly to the Ha412v2 reference genome (https://rieseberglab.github.io/ubc-sunflower-genome/documentation/) usingthe Rieseberg Lab Reproducible Variant Calling pipeline(https://github.com/rieseberglab/snp-calling). Variants were hard filteredto retain retain only bi-allelic SNPs with 90% tranche, MAF>0.01 and genotyperate>50%. Information about each haploblock can be found in Supplementary Table 1.2.2.2 Reference AnnotationsTwo annotations of the Ha412v2 reference genome were used in this analysis:Ha412HOv2.1 and Ha412 Filtered Eugene.Ha412HOv2.1: Ha412HOv2.1 reference annotation was generated using modelsbuilt from known plant proteins and predicted proteins from the published sunflowerreference Ha412HOv1r1, and assembled Ha412HO transcriptomes[14]. MAKER(https://www.yandell-lab.org/software/maker.html), SNAP(https://github.com/KorfLab/SNAP) and AUGUSTUS(http://augustus.gobics.de/) softwares were used to predict genes, and5annotations were improved and refined by rerunning MAKER, SNAP and AUGUSTUSwith EuGene (http://eugene.toulouse.inra.fr/) and EVidenceModeler[6](EVM) gene predictions. Genes were removed if they: had at least 90% identity and 80%coverage (of the gene) for BLAST hits to sunflower transposons, had transcripts shorterthan 50 bp, had mRNAs without protein coding sequences, or contained any mRNAswith CDS having in-frame stop codons. 49,215 genes remained after filtering.Ha412 Filtered Eugene: The Ha412 Filtered Eugene annotation was produced withthe Eugene software. The automated output of EuGene produced 87,728 putative genes.A filtered set of 58,234 genes was produced by removing all transposons that aligned toa gene with 90% identity and over 80% of the length of the gene. Further removal ofgenes containing irregular start and stop codons, and CDS sequences not divisible by 3yielded a filtered count of 57,736 genes.2.2.3 Expression Enrichment TestsFor each SV, genes within the SV boundaries in the Ha412HOv2.1 referenceannotation (+/-5kb) were extracted; genes were included in their entirety as long as anypart fell within the SV region. Genes within each SV were queried against the genomicbackground for increased expression in 11 tissues and in response to 10 hormonetreatments in both roots and leaves using 50 paired-end RNAseq libraries from Badouinet al, 2017[14], and FDR-corrected 10,000x permutation tests. Data availability:https://github.com/katlande/Enrichment_By_Permutations2.2.4 Ha412 Gene OntologyGO pipelines were created for both the Ha412HOv2.1 and Ha412 filtered Eugeneannotations. Three GO libraries were made for the Ha412HOv2.1 gene annotation, andone was made for the Ha412 Filtered Eugene annotation. For Ha412HOv2.1, one librarywas made from TAIR homolog Terms extracted from BLAST, one was made from6blast2GO terms for an older Helianthus reference genome, HanXRQv1.0, and the last wasmade by combining all GO terms from XRQ, TAIR, and Ha412HOv2.1 InterPro2GOterms. For the Ha412 filtered Eugene annotation, only a TAIR homolog GO library isavailable.For each SV, genes within the SV boundaries +/-5kb were extracted. GOenrichment within each SV was conducted by a series of FDR-corrected Fisher’s ExactTests on all terms against the genomic background. Data availability:https://github.com/katlande/Ha412v2.1-Gene-Ontology2.2.5 TAIR Homolog Enrichment ScansFor each haploblock, all genes were extracted and kept only if they werehomologous to a TAIR gene homologous to at least two other genes inside the region ofinterest. Using FDR corrected Fisher’s Exact Tests, each TAIR gene was queried to checkif its Ha412HOv2.1 homologs occur at higher than expected frequencies inside SVregions compared to the genomic background. Data availability: https://github.com/katlande/Enrichment_By_Permutations/blob/main/TAIR_trawler.md2.2.6 dN/dS AnalysisFor each SV, previously haplotyped Wild GWAS individuals[40] were pulled fromHa412 directly aligned VCFs into haplotype-specific VCFs. All SNPs with an allelicfrequency of 0.90 or greater in each haplotype were incorporated into haplotype-specificgene FASTA files, yielding two unique haplotype-specific reference FASTA files for eachgene variant. SNPs from four perennial Helianthus species were used to create a singleancestral sequence for each gene as well.For each gene, an approximate ratio of substitution rates at non-synonymous andsynonymous sites (dN/dS) was found on a codon-by-codon basis. The alignedsequences for both haplotypes were scanned against the ancestral sequence for7haplotype-specific sense and missense mutations, which were used to calculate fixednon-synonymous mutations (Nd) and fixed synonymous mutations (Sd) for each genebetween haplotypes. Genes with fewer than 5 total codon changes were filtered out.During the scan, non-synonymous sites (N) and synonymous sites (S) were alsogenerated for each gene between haplotypes and in comparison to perennial outgroups.dN/dS analyses were conducted in R, using FDR-corrected Fisher’s Exact Tests toidentify all instances where dN/dS was significantly deviant from the neutralassumption. To avoid divide-by-0 errors in cases where no silent mutations werepresent, the direction of selection was calculated as the difference between Nd/N andSd/S over the sum of Nd/N and Sd/S, or ((dN-dS)/(dN+dS)). Data availability:https://github.com/katlande/Haploblock_Gene_Divergence2.2.7 HKAHudson-Kreitman-Aguade´ (HKA) tests were performed by Kaichi Huang usingallelic frequencies from VCFtools (vcftools.sourceforge.net). P-values werecalculated with a Chi-squared test comparing (fixed SNPsgene/polymorphic SNPsgene)and (fixed SNPshaplotype/polymorphic SNPshaplotype).Following this, gene variants with fewer than 6 SNPs were filtered out, and HKAp-values were FDR-corrected. To remove false signals of haplotype-specific divergentselection, candidate variants were further filtered if they contained zeronon-synonymous mutations, or if over 70% of the fixed mutations were shared betweenboth haplotypes.2.2.8 Diversity CalculationsSNP data for diversity calculations used species-wide and haplotype-filtered VCFsgenerated from raw VCFs without perennial sequences. All statistics were calculated inVCFtools using 100kb bins for within-haploblock measurements, and 1mb bins for8genome-wide measurements. Mean values for each were calculated using 10,000xpermutation tests.Nucleotide diversity (⇡) was calculated for each haplotype of each haploblockusing the VCFtools –window-pi function. Genetic diversity (Watterson’s theta) wasestimated using the VCFtools –SNPdensity output divided by an of the subset divided bythe window size. Full species genome-wide values were calculated equivalently.2.3 ResultsResults for this chapter use the Filtered Eugene Ha412HO reference annotation unlessotherwise stated.2.3.1 Functional Enrichments Within HaploblocksBefore investigating differences between haplotypes of these haploblocks, I firstqueried whether the genes in each region were enriched for any specific functions. Threetests were run to identify functional clustering inside haploblocks. The first test queriedgene expression in response to 10 hormonal treatments and in 11 specific tissues in theHa412v2.1 reference annotation. Across all haploblocks, genes were not noticeablyupregulated under any treatment or in any tissue. A full list of enrichment results can befound at: (https://github.com/katlande/Enrichment_By_Permutations/tree/main/Expression_Enrichment).The second test was a gene ontology, querying all genes inside each SV against therest of the genome using GO terms extracted from the TAIR homolog of each gene.P-Values were generated through Fisher’s Exact Test, and after FDR-correction 645 GOterms had p.Adj<0.05 across the 12 haploblocks. See Supplementary Table 1 forinformation about each SV. Highly enriched terms include: recognition of pollen inAnn.11.01 and Pet.11.01, regulation of stomatal closure in Pet.09.01, various immuneterms in Ann.11.01 and Pet.11.01, basipetal auxin transport in Pet.09.01, and regulation9of flavonoid biosynthesis in Ann.05.01 and Pet.05.01. A full list of all 645 enriched GOterms can be found at: (https://github.com/katlande/Ha412v2.1-Gene-Ontology/tree/main/GO_Results)Lastly, genes inside each haploblock were queried for duplications. Clusters of atleast 3 genes with the same TAIR homolog were queried for enrichment within theHaploblock against the genomic background. After FDR-correction, 148 gene clusters inthe Ha412v2.1 reference annotation had p<0.01, and 271 gene clusters in the Ha412Filtered Eugene reference annotation had p<0.01 (Table 2.1).Table 2.1: Total Number of Homologous Gene Clusters Inside Helianthus ssp Haploblocks.Ha412v2.1 Ha412 Filtered EugeneHaploblock Cluster Genes Clusters GenesAnn.01.01 0 0 1 3Ann.05.01 2 12 12 59Ann.11.01 4 19 22 136Ann.13.01 0 0 23 105Ann.15.01 0 0 9 38Arg.06.01 1 3 5 28Arg.10.01 4 16 22 123Petfal.05.01 2 12 13 61Petfal.09.01 1 5 14 58Petfal.11.01 2 12 38 199Petfal.14.01 2 18 34 159Petfal.17.01 0 0 6 21Petpet.05.01 2 12 12 50Petpet.09.01 1 5 14 58Petpet.11.01 2 12 38 199Petpet.17.01 0 0 8 2810Total Enriched Clusters of Homologous Genes by Haploblock. Total number of enriched homol-ogous clusters (Cluster) and total number of enriched clustered genes (Genes) given for two an-notations of the Ha412 reference genome. Min cluster sizes: Ha412v2.1 = 3 genes; Ha412 FilteredEugene = 3 genes. Significance calculated via Fisher’s Exact Test, p.adj < 0.01.This finding does not appear specific to haploblocks. Queries of random 1-100mbchunks of Ha412HOChr02 and Ha412HOChr04 (which lack haploblocks entirely in allspecies) demonstrate that the genomic background is not depleted of homologous geneclusters compared to haploblocks (p>0.1). Nonetheless, many haploblocks contain allhomologs of certain TAIR genes: Ann.13.01 contains all 8 Ha412 homologs ofAT1G47960, a plant cell wall invertase that plays important roles in sugar signalling andstress response. Ann.11.01 and Pet.11.01 similarly contain all 5 Ha412 homologs ofAT4G27160, a seed storage albumin gene. A full list of all clustered, highly homologousgenes can be found at:(https://github.com/katlande/Enrichment_By_Permutations).2.3.2 Haplotype-specific Genetic AlterationsEnriched Functions of Divergent GenesNext, haplotype-specific divergence was compared between alternate haplotypesof each SV. Gene ontology terms from all genes with any amount of expectedhaplotype-specific functional divergence were queried against all genes in thehaploblock in order to identify if any specific gene functions are diverging at a greaterrate than random chance. For the purposes of this test, any gene with at least onehaplotype-specific, fixed, non-synonymous codon change was considered ”functionallydivergent.” After FDR correction, 139 GO terms were enriched for haplotype-specificevolution wherein 15 of a possible 32 SV haplotypes had at least one enriched term.Terms with the most variation by haplotype often appeared highly correlated to local11adaptation. For example, 100% of genes annotated to six immune-related terms inPet.09.01 H. petiolaris fallax haplotype 0 were functionally divergent, as were all genesannotated to osmotic stress and ROS responses. On the other hand, many terms thatwere highly common inside the haploblocks did not show significant divergence. Themost common examples of this include protein phosphorylation, regulation oftranscription, and transmembrane transport, which were frequent in nearly allhaploblocks, but not significantly enriched in missense sites. A full list of enriched GOterms for haplotype-specific gene variants can be found at: (https://github.com/katlande/Ha412v2.1-Gene-Ontology/tree/main/GO_Results).Functions of Predicted Proteins with High Chemical DivergenceTo better identify which genes are most likely functionally divergent betweenhaplotypes, the chemical similarities between predicted protein products of eachhaplotype-specific gene variant were quantified using the Grantham distances betweenthe two sequences. Predicted protein products with larger Grantham distances containpairwise amino acids with greater differences in their chemical properties. Thus, theyare expected to have a greater effect on function[53]. For each haploblock, the topcandidate genes for haplotype-specific functional divergence were determined as thosewith the largest Grantham distances between their haplotype-specific predicted proteinproducts (Table 2.2).Table 2.2: Predicted Protein Products with the Largest Grantham Distance between HaplotypesHaploblockGene(Ha412HO-)GranthamValueTAIR HomologDescriptionLikelyFunctionAnn.01.01 Chr01g0002871 788 ELKS/Rab6-interacting/CAST family protein TranscriptionAnn.05.01 Chr05g0237651 1485 F-box/RNI-like superfamily protein UnknownAnn.11.01 Chr11g0489201 1195histone H3 acetyltransferase thatrecognizes methylated DNA and un-methylated histone H3K4. It prevents DNAhypermethylation of highly homologousmulticopy genes and repetitive sequencesHistonepatterningAnn.13.01 Chr13g0584851 1161 E3 ligase involved in degradationof RHD3 to maintain a tubular ER network.ERdevelopment12HaploblockGene(Ha412HO-)GranthamValueTAIR HomologDescriptionLikelyFunctionAnn.15.01 Chr15g0740631 1269ERF (ethylene response factor), actsas a negative regulator of JA-responsivedefense gene expression and resistance tothe necrotrophic fungal pathogenFusarium oxysporum and antagonizes JAinhibition of root elongation.JA signalling,ImmuneArg.06.01 Chr06g0282581 2001 Disease resistance protein(TIR-NBS-LRR class) family ImmuneArg.10.01 Chr10g0474001 1249 transmembrane protein, putative MembraneProteinPetfal.05.01 Chr05g0235961 925Encodes a plant U-box armadillorepeat protein involved in saltinhibition of germinationSalt Inhibitionof GerminationPetfal.09.01 Chr09g0395771 753 dentin sialophosphoprotein-like protein UnknownPetfal.11.01 Chr11g0494281 1222A repressor of transcriptional genesilencing. Functions by demethylating thetarget promoter DNA. Mutants aremore susceptible to biotrophic pathogensand is repressed in its responsivenessof SA-dependent defence genes.TranscriptionalActivationand ImmunePetfal.14.01 Chr14g0670511 1811 Encodes a WAK-like receptor-like kinase Membrane,signallingPetfal.17.01 Chr17g0811511 796 F-box family protein UnknownPetpet.05.01 Chr05g0238731 875Encodes a major determinant ofvariation flowering time. Confers avernalization requirement causingplants to overwinter vegetatively.FloweringVernalizationPetpet.09.01 Chr09g0395771 1129 dentin sialophosphoprotein-like protein UnknownPetpet.11.01 Chr11g0494281 1546A repressor of transcriptional genesilencing. Functions by demethylating thetarget promoter DNA. Mutants aremore susceptible to biotrophic pathogensand is repressed in its responsivenessof SA-dependent defence genes.TranscriptionalActivationand ImmunePetpet.17.01 Chr17g0811891 847Encodes a protein that is expressedrhythmically and interacts withphytochrome B to control plantdevelopment and flowering. Requiredfor circadian clock regardless of light.CircadianRhythm,FloweringNext, broader trends in the gene functions with the greatest haplotype-specificchemical divergence were examined. Across all haploblocks, genes with non-zeroGrantham distances were annotated with their TAIR homolog GO terms. The Granthamdistances of individual GO terms within a haploblock were generated by summing theGrantham values of all genes annotated to those GO terms. The 25 most intenselydivergent GO terms across all haploblocks were extracted and examined (Figure 2.1).13Figure 2.1: Enrichment of the 25 Most Divergent GO Terms as a Function of Percentage of TotalGrantham Distance for each HaploblockIntensity of the total Grantham Distance between haplotype-specific predicted protein productsfor each Haploblock as a function of the percentage of total Grantham distances between allhaplotype-specific gene variants. Four intensities of enrichment as a percentage of all divergencein the haploblock: <0.1%, 0.1%-1%, 1%-5%, >5%.Across all haploblocks, the most commonly divergent GO terms fell into just a fewmain categories: abiotic and biotic stress response terms, hormone response (ethylene,auxin, ABA) terms, reproduction and development terms, and terms related to theregulation of transcription, protein modification, and other cellular processes. Notably,the finding that Ann.01.01 and Ann.13.01 do not have haplotype-specific changes ingenes related to osmotic stress is supported by greenhouse drought trials that found no14haplotype-specific drought adaptation between haplotypes of these SVs, despite theirapparent distribution along a precipitation cline (Supplementary Figure 1).GO terms with the largest Grantham values within individual haploblocksgenerally fell in line with overall trends, barring a few notable exceptions. For example,terms associated with lignin and flavonoid biosynthesis in Ann.05.01 and Pet.05.01 hadvery high summed Grantham values. A full list of haploblock-specific GO termGrantham sums is available at:(https://github.com/katlande/Haploblock_Gene_Divergence).To distinguish whether the most highly divergent terms inside the haploblockswere distinct from the type of functions expected to diverge in the sunflower genomegenerally, a background set of five randomly selected, 30mb, non-haploblock regionswere extracted (Ha412HOChr01:101.5-131.5mb, Ha412HOChr05:50.6-80.6mb,Ha412HOChr10:112.2-142.2mb, Ha412HOChr11:70.3-100.3mb,Ha412HOChr12:55.9-85.9mb). For each species and subspecies, genes in these windowswere compared against the perennials, and the Grantham distances for each term werefound. As a larger number of total genes reside in the SV regions than the controlregions, the raw Grantham sums of each term were non-comparable. Instead, each termwas ranked from largest to smallest Grantham distance, and the ranks of thehaploblocks were compared to those of the genomic background.The top 25 terms in Figure 2.1 had generally similar ranks in the genomicbackground, with a few exceptions. Terms with comparatively high ranks between SVhaplotypes include: vegetative to reproductive phase transition of meristem, cellularresponse to hypoxia, response to cold, recognition of pollen, proteinautophosphorylation, and response to wounding.Across all GO terms that appeared in both the genomic background and thehaploblocks, the terms with the most divergent rankings were extracted (Table 2.3).Terms with the highest comparative rank differential between SV haplotypes include15terms related to lignin biosynthesis, flower development, pollen development, and DNAmethylation, among others.Table 2.3: GO Terms with the Largest Grantham Distances in Haploblocks Compared to theGenomic BackgroundGO TermSVGranthamSumSVGranthamRankGenomicGranthamSumGenomicGranthamRankRankDifferentiallignin biosyntheticprocess 9288 28 644 757 0.929plant-typehypersensitive response 7289 40 693 731 0.896regulation oftiming of transition fromvegetative to reproductive phase7974 34 1076 480 0.868regulation ofDNA methylation 6176 58 752 699 0.847SCF-dependent proteasomalubiquitin-dependentprotein catabolic process7183 42 1270 406 0.812recognition of pollen 28777 4 5566 35 0.795vernalization response 7324 39 1514 327 0.787proteinautophosphorylation 32881 3 7153 25 0.786photomorphogenesis 6959 46 1354 370 0.779DNA demethylation 5229 77 862 618 0.778vegetative to reproductivephase transition of meristem 10327 20 2652 156 0.773sugar mediatedsignaling pathway 6188 56 1221 423 0.766base-excision repair 3798 141 60 1053 0.764lipid metabolic process 9470 25 2371 178 0.754response to heat 7035 43 1612 303 0.752systemic acquired resistance 5763 65 1154 446 0.746trichome differentiation 5948 63 1259 409 0.733regulation of hydrogenperoxide metabolic process 4315 105 772 676 0.731negative regulationof flower development 8180 33 2167 200 0.717hyperosmoticsalinity response 3986 123 670 742 0.716pollen wall assembly 3949 126 647 754 0.714DNAmediatedtransformation 3719 148 525 834 0.699regulation of secondarycell wall biogenesis 5048 84 1122 460 0.691spindle assembly 4399 101 973 545 0.688potassium iontransmembrane transport 4387 103 952 555 0.687Top 25 GO terms with the largest rank differential between SV-haplotype Grantham distancesand annual-perennial Grantham distances. Rank differential calculated as (SV Rank - GenomicRank)/(SV Rank + Genomic Rank)16On the other hand, terms with the highest rank differentials in the genomic backgroundwere generally related to auxin signalling, cellular metabolism, and cellulardetoxification, and the cytoskeleton and cell cycle. Terms with the most similar ranksbetween the comparisons included terms related to transmembrane transport, ubiquitinmetabolism, root development, sterol biosynthesis, and heat acclimation. A full list ofGrantham distance ranks between the two comparisons is available at:(https://github.com/katlande/Haploblock_Gene_Divergence).Haplotype-Specific Stop Codon AlterationsNotably, stop codon alterations do not affect Grantham values despite their largeexpected impact on the functionality of predicted protein products. As such, genes withhaplotype-specific stop codon alterations were examined separately. While over half thethe genes with stop codon alterations do not have TAIR homologs, the functions of thosethat do appear related to local adaptation. Examples of this include: immune genes inAnn.11.01, Pet.11.01, and Petfal.09.01, giberellic acid signalling genes in Pet.11.01, and acalcium ion uptake gene in Petfal.09.01, among others (Supplementary Table 3).Other Trends in Haplotype-Specific Gene VariantsBroadly speaking, one haplotype of each SV has much more fixed variation thanthe other. FDR-corrected pairwise t-tests between haplotype-specific silent mutationfixation rates were conducted to identify the extent of this deviation (Table 2.4).Across all haploblocks, the rate of fixation of expected neutral sites was highlyvariable, suggesting that divergent haplotypes of all haploblocks have distinctpopulation sizes, origins, and/or evolutionary forces acting on them.17Table 2.4: Silent Mutation Fixation Rates between HaploblocksHaploblock Fixed SilentHaplotype 0Fixed SilentHaplotype 2 p.AdjSignificancelevelAnn.01.01 171 96 4.3e-03 *Ann.05.01 866 459 3.4e-18 ***Ann.11.01 794 969 3.1e-02 *Ann.13.01 466 874 1.9e-21 ****Ann.15.01 586 381 2.1e-08 **Arg.06.01 337 179 1.3e-05 *Arg.10.01 405 1319 6.8e-40 ****Petfal.05.01 1160 285 1.5e-42 ****Petfal.09.01 286 556 4.1e-12 ***Petfal.11.01 924 619 2.7e-09 **Petfal.14.01 1459 662 5.5e-33 ****Petfal.17.01 253 171 1.8e-02 *Petpet.05.01 873 333 1.2e-24 ****Petpet.09.01 319 752 1.2e-24 ****Petpet.11.01 1544 713 2.0e-33 ****Petpet.17.01 294 225 4.6e-02 *Number of fixed mutations between the same gene variants in alternative haplotypes of each hap-loblock. Significance calculated as FDR-corrected p-value of paired Wilcoxon Tests of haploblock-wide synonymous site fixation events between haplotypes. Significance: p<0.05*, p<1e-05**,p<1e-10***, p<1e-20****.2.3.3 Population Genetics of Divergent HaplotypesHaplotype-Specific Nucleotide DiversityTo further investigate the cause of the striking variation in silent mutation ratesbetween alternative haplotypes of the haploblocks, ⇡ diversity was calculated toestimate the amount of polymorhpism in each haplotype (Table 2.5). For H. argophylus,H. petiolaris petiolaris, and H. petiolaris fallax, ⇡ diversity is larger in the haplotype with asmaller number of fixed mutations. However, the opposite trend is seen in H. annuus,where all haploblocks barring Ann.11.01 have greater ⇡ diversity in the haploblock witha great number of fixed silent mutations.To estimate the effective population size of each SV haplotype, the SNP densities ofgenomic bins containing entirely non-coding sequences were used to estimate18Table 2.5: Pi Diversity versus Fixed Silent Mutation Frequency between Haploblock HaplotypesHaploblock Mean ⇡Haplotype 0Mean ⇡Haplotype 2Larger⇡GreaterSdAnn.01.01 6.27e-04 5.08e-04 Hap0 Hap0Ann.05.01 5.46e-04 3.86e-04 Hap0 Hap0Ann.11.01 4.71e-04 2.53e-04 Hap0 Hap2Ann.13.01 4.52e-04 4.80e-04 Hap2 Hap2Ann.15.01 2.90e-04 2.69e-04 Hap0 Hap0Arg.06.01 8.07e-05 1.41e-04 Hap2 Hap0Arg.10.01 5.17e-04 3.34e-04 Hap0 Hap2Petfal.05.01 2.13e-04 3.48e-04 Hap2 Hap0Petfal.09.01 2.71e-04 2.30e-04 Hap0 Hap2Petfal.11.01 2.10e-04 2.48e-04 Hap2 Hap0Petfal.14.01 1.24e-04 2.04e-04 Hap2 Hap0Petfal.17.01 2.64e-04 3.44e-04 Hap2 Hap0Petpet.05.01 2.58e-04 3.75e-04 Hap2 Hap0Petpet.09.01 2.73e-04 2.12e-04 Hap0 Hap2Petpet.11.01 1.68e-04 2.53e-04 Hap2 Hap0Petpet.17.01 2.69e-04 3.17e-04 Hap2 Hap0Average ⇡ diversity in both haplotypes of all haploblocks compared to the frequency of fixedmutations. Distributions of binned Pi values were all highly distinct, with FDR-corrected two-sided t-test p-values = 0.Watterson’s Theta (✓W ) for both haplotypes of each haploblock, as well as eachchromosome of the full species. Under neutral drift, assuming an equal mutation ratebetween haploblocks and the genomic background, the effective population size of eachSV haplotype can be estimated simply as a ratio between ✓Haplotype and ✓Species (Equation1.1).✓1✓2=4Ne1µ4Ne2µ=Ne1Ne2(2.1)The ratios of ✓W between haplotypes of each haploblock were generally in line withthe ⇡ diversity data (Table 2.6). In H. annuus, only Ann.11.01 had a smaller ✓W in thehaplotype with a greater number of fixed silent mutations. Moreover, all haploblocks inH. argophyllus, H. petiolaris petiolaris, and H. petiolaris fallax had a smaller ✓W in thehaplotypes with a greater number of fixed silent mutations as predicted by ⇡, with the19Table 2.6: Watterson’s Theta and Effective Population Size Estimates for HaploblocksHaploblock ✓Sp ✓Hap0 ✓Hap2✓Hap0/✓Sp✓Hap2/✓SpLarger ✓Ann.01.01 5.00e-04 6.82e-04 3.98e-04 1.36 0.80 Hap0Ann.05.01 4.60e-04 5.39e-04 3.74e-04 1.17 0.81 Hap0Ann.11.01 4.33e-04 6.02e-04 1.93e-04 1.39 0.45 Hap0Ann.13.01 5.51e-04 4.37e-04 5.54e-04 0.79 1.01 Hap2Ann.15.01 4.20e-04 3.31e-04 2.43e-04 0.79 0.58 Hap0Arg.06.01 1.78e-04 1.06e-04 7.78e-05 0.60 0.44 Hap0Arg.10.01 2.45e-04 4.60e-04 2.12e-04 1.88 0.87 Hap0Petfal.05.01 1.52e-04 1.31e-04 3.50e-04 0.86 2.30 Hap2Petfal.09.01 2.11e-04 2.37e-04 1.22e-04 1.12 0.58 Hap0Petfal.11.01 1.46e-04 1.23e-04 2.34e-04 0.84 1.60 Hap2Petfal.14.01 1.25e-04 6.00e-05 1.61e-04 0.48 1.29 Hap2Petfal.17.01 1.15e-04 1.60e-04 2.03e-04 1.39 1.77 Hap2Petpet.05.01 1.25e-04 1.69e-04 2.74e-04 1.35 2.19 Hap2Petpet.09.01 1.77e-04 1.76e-04 1.12e-04 0.99 0.63 Hap0Petpet.11.01 1.36e-04 1.13e-04 1.61e-04 0.83 1.18 Hap2Petpet.17.01 9.53e-05 1.57e-04 1.33e-04 1.65 1.40 Hap0For each haploblock, ✓Sp is the mean ✓W value for non-coding, non-haploblock regions of thechromosome with data from all sequenced individuals in the species. H. annuus=614. H. argophyl-lus=299, H. petiolaris petiolaris=168, H. petiolaris fallax=259.exception of Arg.06.01 and Petpet.17.01. More notably, in nearly all cases, one or bothhaplotypes of these haploblocks had a greater ✓W than the species-wide value, despitemaking up only a subset of the population.2.3.4 Evolutionary Forces Acting on Haplotype-Specific Gene VariantsGene-wide dN/dSTo further investigate evolutionary forces acting on individual genes, a dN/dSanalysis was performed to identify whether genes appear to be diverging due to positiveselection, negative selection, or neutral drift. dN/dS values were generated for bothhaplotype-specific gene variants for all SVs, using a consensus of four perennial speciesas an ancestral sequence. The perennials were chosen as ancestral lineages as their20divergence from H. annuus, H. argophyllus, and H. petiolaris predates the origin of thehaploblocks[40].Figure 2.2: Plot of dN/dS of Fixed Sites vs. p-Value for all Haplotype-specific Gene VariantsTotal gene variants = 24,634. Positive: 1,971 (8.0%); negative: 7,725 (31.4%); no change: 14,938(60.6%). Total gene variants with p<0.01: 1,120; p<1e-05: 96; p<1e-10: 5.Broadly, genes with a greater number of fixed missense mutations than expectationunder random chance (dN/dS>1) are assumed to be under divergent selection.Conversely, those with fewer missense mutations than expected by chance (dN/dS<1)are assumed to be under purifying selection. Genes with a frequency of sense andmissense mutations similar to what would be expected by chance are assumed to beunder neutral genetic drift. At the gene-wide level, no statistically significant signals ofdN/dS > 1 could be detected (Figure 2.2). This is likely due to the low number of fixeddifferences between the closely related haplotypes of these SVs. The most likelycandidate for a statistically significant dN/dS > 1 in the gene-wide data isHa412HOChr13g0585511, a homolog of an Arabidopsis light-responsive transcriptionfactor, in haplotype 0 of Ann.13.01 with an un-adjusted Fisher’s p-value of 0.13.On the other hand, signals of purifying selection were rampant throughout thehaploblocks, with 1,584 haplotype-specific gene variants from all haploblocks21demonstrating statistically significant signals of dN/dS<1 (FDR-corrected Fisher’sp-value<0.05). dN/dS data for all gene variants is available at:(https://github.com/katlande/Haploblock_Gene_Divergence).dN/dS in 100kb binsdN/dS analysis was subsequently performed in 100kb bins in an attempt toamplify possible signals of divergent selection that were rendered insignificant by lownumbers of fixed missense mutations. However, the same trend as the gene-widedN/dS was uncovered. No bins displayed significant signals of dN/dS > 1, while 1,049bins displayed statistically significant signals of dN/dS<1.Transition/Transversion of Polymorphic SNPsDue to the unexpectedly large genetic diversity metrics in SV haplotypes, thepossibility of balancing selection cannot be excluded. However, dN/dS exclusivelylooks at fixed mutations, and is blind to balancing selection which definitionally occursin polymorphic sites. Thus, to check whether balancing selection is maintainingfunctionally divergent gene variants at polymorphic levels inside the haploblocks, thetransition/transversion ratio of polymorphic sites (pN/pS) in each haplotype-specificgene variant was extracted and compared to its dN/dS value in a Mcdonald-Kreitman(MK) test. A higher Transition/Transversion (Ka/Ks) in the polymorphic SNPs than thefixed SNPs of a gene is indicative of balancing selection. On the other hand, if ratio ofmissense to sense mutations in the fixed SNPs is larger than that of the polymorphicSNPs, it is indicative of divergent selection.To reduce statistical noise in the MK test, gene variants with low variability werefiltered out. All variants with fewer than 10 fixed and polymorphic SNPs respectively,and a total SNP count below 40, were removed. 1,031 variants remained after filtering, ofwhich only 7 had a pN/pS larger than 1. Moreover, 5 variants had a MK p-value<0.05after FDR-correction. Of these, 1 had a larger polymorphic site Ka/Ks, suggesting22balancing selection, and the other four had a larger fixed site Ka/Ks, suggestingdivergent selection (Table 2.7).Table 2.7: Significant Mcdonald-Krietman Test GenesGene Hap 0 Hap2(Ha412HO-) Haploblock p-Adj Np/Sp Nd/Sd p-Adj Np/Sp Nd/Sd HomologChr06g0282111 Arg.06.01 0.013 29/21 1/21 NS 25/21 0/6 AT1G73590Chr11g0498941 Petpet.11.01 0.013 9/34 12/2 0.041 9/39 11/4 AT4G15570Chr11g0498941 Petfal.11.01 NS 20/36 2/1 0.041 15/57 11/4 AT4G15570Chr11g0489311 Petfal.11.01 NS 13/37 5/2 0.041 16/68 9/3 AT1G53210Genes with significantMcdonald-Krietman p-values after FDR-correction to p<0.05. Np/Sp (non-sense/sense polymorphic sites) and Nd/Sd (nonsense/sense fixed sites) given for both haplo-types.Ha412HOChr06g0282111 is a strong candidate for balancing selection. On top of astatistically-significant MK test and a pN/pS>dN/dS, the haplotype 0 and 2 variants ofthis gene in Arg.06.01 contain 30 and 25 non-synonymous SNPs respectively, 24 of whichare shared. The TAIR homolog of Ha412HOChr06g0282111 is PIN1 (AT1G73590), anauxin efflux carrier with important roles in root and shoot development and organpatterning. Arabidopsis individuals with mutations in this gene typically have strikingphenotypes: lack of flowers, reduced leaf number, aberrant leaf shape, yellow seeds, andlack of trichomes on stem base and leaves.Moreover, Ha412HOChr11g0498941 and Ha412HOChr11g0489311 show potentialsignals of divergent selection in Petpet.11.01 and Petfal.11.01, and Petfal.11.01respectively. In all cases, both haplotype-specific gene variants have a dN/dS>pN/pS.Haplotype-specific gene variants of Ha412HOChr11g0498941 andHa412HOChr11g0498941 in H. petiolaris fallax are highly distinct. However, thehaplotype-specific gene variants of Ha412HOChr11g0498941 in H. petiolaris petiolaris arehighly similar, suggesting selection on this gene may have occurred before thehaplotypes split. The TAIR homolog of Ha412HOChr11g0489311 is NCL (AT1G53210), aNa+/Ca 2+ exchanger-like protein that is associated with Ca2+ homeostasismaintenance. On the other hand, the homolog of Ha412HOChr11g0498941 is MAA323(AT4G15570), a splicing endonuclease involved in female gametophyte development;mutants are female gametophyte defective. MK test results for all haplotype-specificgene variants can be found at:(https://github.com/katlande/Haploblock_Gene_Divergence).HKAA Hudson-Kreitman-Aguade´ (HKA) test was also preformed on thehaplotype-specific gene variants. HKA compares the ratio of a gene’s fixed sites to itspolymorphic sites against the ratio of fixed all sites in the haplotype against allpolymorphic sites in the haplotype. Enrichments in a gene’s fixed sites are suggestivethat the gene was subject to a selective sweep. Moreover, enrichments in polymorphismare suggestive that the gene is under balancing selection.After FDR-correction to p<0.01 and filtering for false positives, 310 gene variantsacross 16 haploblocks displayed significantly higher divergence compared topolymorphism (fixedgene/fixedtotal > polymorphicgene/polymorphictotal): evidence ofdirectional selection. On the other hand, 47 gene variants across 9 haploblocks displayeda significant p-value in the inverse direction: evidence of balancing selection. (Table 2.8).Table 2.8: Significant HKA genes by SV Haplotype with GO TermsD>P D<PHaploblock Hap 0 Hap 2 Hap 0 Hap 2Ann.01.01 0 1 0 1Ann.05.01 11: NS10: glycoside transport,stem and cotyledonvascular patterning,pollen wall assembly0 0Ann.11.01 10: NS 33: signal transduction,recognition of pollen 0 2Ann.13.01 21: NS 10: NS 0 2Ann.15.01 14: xylem and phloempattern formation14: xylem and phloempattern formation1 0Arg.06.01 0 7: NS 5 2Arg.10.01 3 6: NS 8: NS 16: NSPetfal.05.01 20: NS 6: NS 5 0Petfal.09.01 4 6: regulation ofstomatal closure 0 024Petfal.11.01 12: cellular response tophosphate starvation 13: NS 0 0Petfal.14.01 18: chromatin silencing10: protein auto-phosphorlyation, cellsurface receptor signaling3 0Petfal.17.01 2 2 0 0Petpet.05.01 5 16: NS 0 0Petpet.09.018: response to chitin, rootdevelopment, regulationof stomatal closure17: NS 0 0Petpet.11.01 6: NS 20: responses to: ABA,oxidative stress, wounding 0 2Petpet.17.01 1 4 0 0Number of genes with a significant D>P or D<P and their enriched GO terms com-pared to the SV background (FDR-corrected Fisher’s p-value<0.05). D=(fixedgene/fixedtotal)and P=(polymorphicgene/polymorphictotal). HKA significance: FDR-corrected Chi-Squared p-value<0.01. Table separated by direction of selection, haplotype, and haploblock. GO conductedon haploblocks with >5 significant genes.These results suggest that divergent selection is frequent: directly at odds with theresults of the Ka/Ks analyses. Forty-one gene variants displaying a significantly highfixed to polymorphic ratio in HKA also have a statistically significant dN/dS<1. On theother hand, consistent with the MK tests is the result that the strongest signals ofbalancing selection occur in H. argophyllus haploblocks. Additionally, genes with asignificant excess of fixed SNPs tend to have annotations to GO terms with largehaplotype-specific Grantham changes, such as: recognition of pollen in Ann.11.01 SVs,responses to ABA and wounding in Petpet.11.01, chromatin silencing in Petfal.14.01, andresponse chitin and regulation of stomatal closure in Petpet.09.01. A full list of HKAresults can be found at:(https://github.com/katlande/Haploblock_Gene_Divergence/).Genes with significantly higher divergence compared to polymorphism areexpected to have undergone recent selective sweeps. To further understand the traitsthat seem to be under haplotype-specific selection, the haplotype-specific gene variantswith the most significant p-value were extracted (Table 2.9).25Table 2.9: Top Candidate Genes for Selective Sweep in Each HaploblockHaploblockGene(Ha412HO-)Homolog p.Adj Annotation HapAnn.01.01 NA NA NA NA 0Chr01g0002631 AT3G63010 1.38e-06 (GA) receptor 2Ann.05.01 Chr05g0232781 AT1G75540 5.13e-26Encodes a B-box zinc fingertranscription factor BBX21 thatinteracts with COP1 to control de-etiolation and shade avoidance.0Chr05g0231241 AT4G36810 8.02e-39Geranylgeranyl pyrophosphatesynthase involved inisoprenoid biosynthesis.2Ann.11.01 Chr11g0489731 AT4G04910 2.52e-21 N-ethylmaleimide sensitive factor 0Chr11g0491321 AT4G27290 2.06e-23 S-locus lectin kinase 2Ann.13.01 Chr13g0591071 AT4G39530 1.67e-29 Tetratricopeptide repeat-like 0Chr13g0585731 AT4G12680 5.03e-11 transmembrane protein 2Ann.15.01 Chr15g0737461 AT4G36890 4.05e-08 Essential for xylan elongationin seed coat mucilage0Chr15g0737481 AT5G67250 1.55e-23 Related to growthand auxin response2Arg.06.01 NA NA NA NA 0Chr06g0281361 AT5G36260 2.15e-05 aspartyl protease 2Arg.10.01 Chr10g0467671 AT5G57130 1.62e-07Has weak similarity tochaperonins required forthermotolerance0Chr10g0477201 AT2G19910 3.13e-05 RNA-dependent RNA polymerase 2Petfal.05.01 Chr05g0236251 AT3G48195 5.76e-12 sorting nexin 0Chr05g0243211 AT1G18740 5.11e-17Cold-induced, loss of functionmutants are more sensitiveto freezing and havereduced levels of CBFs2Petfal.09.01 Chr09g0402331 AT5G16530 6.41e-04 Auxin transporter 0Chr09g0393021 AT3G25400 3.43e-12 dCTP pyrophosphatase-like 2Petfal.11.01 Chr11g0491821 AT4G27190 2.82e-25 NB-ARC diseaseresistance protein0Chr11g0493791 AT4G27290 6.80e-21 S-locus lectin kinase 2Petfal.14.01 Chr14g0674071 AT3G28345 8.58e-14 ABC transporter instem vascular tissue0Chr14g0674071 AT3G28345 3.48e-56 ABC transporter instem vascular tissue2Petfal.17.01 Chr17g0815861 AT2G30800 3.38e-05helicase expressed spec-ifically in tapetumand vascular tissue0Chr17g0815301 AT4G21410 8.27e-04 cysteine-rich receptor-like protein kinase2Petpet.05.01 Chr05g0240261 AT4G27240 1.03e-03 zinc finger protein 0Chr05g0240571 AT3G20540 1.29e-10 Organellar DNA polymerase Iinvolved in DSB repair2Petpet.09.01 Chr09g0393021 AT3G25400 8.56e-10 dCTP pyrophosphatase 026Chr09g0396601 AT5G06710 4.03e-12 Homeobox-leucine zipper 2Petpet.11.01 Chr11g0493791 AT4G27290 3.62e-08 S-locus lectin kinase 0Chr11g0491821 AT4G27190 6.06e-10 NB-ARC diseaseresistance protein2Petpet.17.01 Chr17g0815301 AT4G21410 2.13e-11 cysteine-rich receptor-like kinase0Chr17g0811511 AT3G06240 4.18e-07 F-box family protein 2Genes with the smallest adjusted HKA p-value and D>P where D=(fixedgene/fixedtotal) andP=(polymorphicgene/polymorphictotal), annotated with TAIR homologs and their annotations.2.4 Discussion2.4.1 Functional Clustering Inside HelianthusHaploblocksBoth gene ontology and homolog clustering enrichment tests demonstratefunctional clustering amongst genes inside Helianthus haploblocks. This clustering doesnot appear to be a haploblock-specific phenomenon, as tandem duplications[12], andresulting genetic redundancy[39] and neofunctionalization[60] are common inangiosperms. While clustered terms do not appear more likely to be functionallydivergent as a result of single nucleotide polymorphisms (Supplementary Figure 2), thishighly clustered architecture of the Helianthus genome appears to allow novelhaploblocks to capture many genes with similar functions, or genes that act in the samepathways. Notable examples of this include the large cluster of flavonoid biosynthesisgenes in Ann.05.01 that show high haplotype-specific divergence, and the cluster of 5genes highly homologous to the A. thaliana immune gene AT4G27190 in Ann.11.01,wherein two copies contain haplotype-specific stop codon alterations.Previous studies have found that alterations to duplicated gene clusters withinhaploblocks can create haplotype-specific phenotypes. In H. argophyllus, 4 HaFT(Flowering Locus-T) genes can be found within the Arg.06.01 haploblock. An apparentdeletion of one copy in one of the haplotypes is responsible for a 77 day difference in27flowering time between haplotypes[40]. The analyses in this thesis are not suited fordetecting large deletions. However, comparing the putative functions of these geneclusters to GWAS and GEA data from Todesco et al 2020, there is some indication thatthese highly homologous gene clusters correlate with some haplotype-specific functionaldivergence between SV haplotypes.For example, divergent haplotypes of Pet.11.01 in H. petiolaris fallax are known to bedifferentially adapted to dune ecosystems through divergent seed morphology[40].Perchance, this haploblock also contains all five Ha412 homologs of AT4G27160, seedstorage albumin 3. Another example occurs in the H. annuus haploblock Ann.15.01,which is known to be associated with total plant height[40]. Ann.15.01 contains five of theten Helianthus genes highly homologous to giberellin 20-oxidase (AT4G25420), agiberellin biosynthetic enzyme which causes dwarfism when silenced in Arabidopsis [63].2.4.2 Sequence Divergence between SV HaplotypesDespite the wide variety of divergent phenotypes and ecosystems associated withalternate haplotypes of these SVs, a small number of GO terms are able to describe alarge portion of the predicted functional divergence between haplotype-specific aminoacid sequences of these haploblocks. Predicted alterations in putative transcriptionregulators, kinases, and ubiquitylases suggest a great deal of downstream divergence inexpression, signalling, and protein modification that cannot be measured by DNAsequence alterations alone. Moreover, a variety of biotic and abiotic stress responseterms were highly divergent between haplotypes of all SVs. Predicted functionaldivergence between haplotype-specific protein products was broadly enriched for termsrelated to local adaptation such as response to salt stress, response to water stress,defense response to fungus, and many others. Though many of these terms do notappear to be specifically divergent inside the SVs compared to the rest of the genomicbackground, they are nonetheless highly divergent in a haplotype-specific manner.Moreover, some terms related to locally adapted lineages appear preferentially divergent28compared to the genomic expectation, such as response to heat, vernalization response,and lignin biosynthesis.Comparing the terms with the largest Grantham Distances in individualhaploblocks to GWAS and GEA data further suggests some haplotype-specificphenotype divergence may result from the identified alterations to these genes. Manyhaploblocks with strong GEA temperature correlations also have high expecteddivergence in immune genes (Ann.11.01, Petfal.17.01, Petpet.09.01, Petpet.11.01) and/orcold stress response genes (Ann.15.01, Arg.10.01, Petfal.17.01, Petpet.17.01).Additionally, many haploblocks with GEA signals for soil salt metrics had largeGrantham Distances between genes related to salt stress (Petfal.09.01 and Petfal.11.01).Both Ann.15.01 and Petfal.05.01 had GWAS signals for flowering and/or budding timedivergence, which could be explained by alterations to ethylene signalling genes inAnn.15.01[49], and lignin biosynthesis genes in Petfal.05.01[51]. Finally, Petpet.09.01 hadGWAS signals for a variety of leaf morphology divergence, possibly explained bypredicted functional divergence in leaf senescence genes. A full list of all divergent GOterms between SV haplotypes is available at:(https://github.com/katlande/Haploblock_Gene_Divergence).Genes with stop codon alterations are even more closely tied to projected GWASphenotypes and GEA conditions. For example, Ann.13.01 showed strong GWAScorrelation to flowering time traits, and has a stop codon alteration in a gene with highhomology to AT2G45660, a highly conserved[30] Arabidopsis flowering time regulator[18].Petfal.09.01 has a GEA hit for soil calcium, and also has a stop codon alteration in a Ca2+uptake gene. Pet.11.01 has stop codon alterations in giberellic acid signalling genes,potentially explaining the strong GWAS signals for plant height metrics in both the H. p.petiolaris and H. p. fallax variants of the SV[40].All told, the predicted functional differences between haplotype-specific genevariants of these SVs appear to be rich with mutations that may be related to localadaptation, despite the small scope of this analysis. However, no definitive statements29can be made based on bioinformatic data alone, and going forward molecular studieswould be required to verify any hypotheses put forward about specifichaplotype-specific gene functions.2.4.3 Population Genetics of SV HaplotypesPatterns of Genetic Variation and Divergence within Helianthus SVsFor all haploblocks, one haplotype had significantly more fixed silent mutationsthan the other (Table 2.4). A possible explanation for this pattern, which is supported byphylogenetic data[40], is that the divergent haplotypes originated via introgression withother, sometimes extinct, sunflower species.Despite their apparently similar origins, the genetic diversity of the divergenthaplotypes differed across species. In H. argophyllus and H. petiolaris, genetic diversitywas consistently lower in the divergent haplotypes (except for Petpet.17.01), whereas theopposite trend was seen in all H. annuus samples (barring Ann.11.01), wherein the moredivergent haplotype had more genetic diversity. This pattern is consistent withhaplotype frequencies: the haplotype found at a higher frequency within the species orsubspecies typically had higher genetic diversity, consistent with expectations fromneutral theory. There were two exceptions to this general trend: Ann.05.01 andPetpet.11.01). For Ann.05.01, the two haplotypes differed only slightly in frequency (0.48versus 0.52), perhaps explaining the discrepancy for this haplotype. Petpet.11.01 wasalso unusual in that haplotype 2 was the more frequent of the two haplotypes in H.petiolaris fallax, but not in H. petiolaris petiolaris. If haplotype frequencies for the twosubspecies were combined, then the more frequent haplotype (haplotype 2) also has thehighest genetic variation.So why are divergent (introgressed haplotypes) more frequent / widely distributedin H. annuus, but not in H. argophyllus and H. petiolaris? The introgressed haplotypestypically offer adaptation to more extreme habitats: drier habitats in H. annuus, barrier30islands in H. argophyllus, and sand dunes in H. petiolaris. The barrier islands and sanddunes are restricted geographically, leading to lower species-wide frequencies for thesehaplotypes. In contrast, the drier habitats favored by the divergent H. annuus haplotypeare widespread across western North America, offering ample room for the spread ofthese haplotypes.Forces of Selection within HaploblocksDespite ample evidence in the literature that non-recombining structural varianthaplotypes can undergo differential adaptation[41] [11] [42] [36], as well as evidence thatHelianthus ssp. haploblocks are divergently adapted to specific environments[40], Ka/Ksdata broadly suggests that the primary evolutionary force acting in these SVs ispurifying selection, but lacks the power to make definitive claims about the roles ofgenetic drift and divergent selection. Conversely, the MK and HKA tests suggestselective sweeps and balancing selection are widespread across these SVs.These conflicting results may be caused by Ka/Ks being under-powered. Whenphylogenetic distance is short, dN/dS violates the assumption that each codonsegregates independently[10]. Moreover, even though recombination rates betweenequivalent haplotypes of these SVs are not diminished, recombination in SVs is expectedto be near 0 in heterozygous individuals[40]. In effect, this reduces the population-wideaverage recombination rate of SVs, as wild individuals are commonly found inpopulations that are polymorphic for SV haplotypes. Reduced recombination isexpected to increase effects of genetic hitchhiking[54], potentially biasing Ka/Ks evenmore. Thus, genes with Ka/Ks<1 may actually be under strong positive selection[58]. Inaddition to explaining a lack of evidence of divergent selection in the dN/dS, this couldalso explain why 41 genes displaying significant signals of negative selection in thedN/dS displayed putative signals of divergent selection in the HKA.Haplotype-Specific Selective Sweeps31Results from the HKA indicate that haplotype-specific sweeps have occurred innearly every haplotype of all haploblocks, suggesting that divergent selection is drivinggenetic evolution between SV haplotypes. Moreover, in haploblocks with enoughsignificant genes to conduct a GO analysis, significantly enriched GO terms are generallyrelated to stress responses and development.Balancing Selection in H. argophyllusBalancing selection is known to maintain alternate inversion haplotypes in genepools. Specifically, this occurs when the haplotypes are adapted to different selectionpressures[9]. This is reminiscent of the SVs studied here: polymorphic despite broadlyancient divergence times paired with strong evidence of locally adapted haplotypes[40].While balancing selection between haplotypes is likely maintaining alternatehaplotypes of these SVs for the aforementioned reasons, balancing selection actingwithin individual haplotypes is expected to be fairly uncommon[1]. Moreover, theanalyses in the present study were specifically looking for signals of balancing selectionacting on haplotype-specific gene variantswithin lineages.Despite their hypothesized rarity, signals of balancing selection were detectable inthe majority of SVs at the single gene level. In total, 47 gene variants display astatistically significant enrichment in polymorphism in the HKA. Of these, 6 come fromfour H. annuus haploblocks, 10 come from three H. petiolaris haploblocks, and the other31 come from just two H. argophyllus haploblocks. However, because much of thepolymorphism is maintained in both haplotype-specific gene variants, it is likely thatthese signals represent selection events that predate the origin of these SVs. Further, theputative functions of specific genes under balancing selection are generallynon-descriptive, and no GO term enrichment was found in any SV. Thus, it is difficult tohypothesize what role these genes play.322.5 ConclusionOverall, there are a substantial number of haplotype-specific coding mutations inthese SVs, many of which appear potentially explanatory of specific phenotypes,ecotypes, or related to local environments as described in Todesco et al, 2020. However,CDS changes alone are not indicative of phenotypic change, and functional annotationsfrom distant taxa are expected to be imperfect. Thus, while this research identifies a suiteof candidate genes for these divergent phenotypes, no direct causative links can bedrawn.Moreover, these data suggest that positive selection is driving the adaptivedivergence of haplotypes to different environments leading the maintenance of theseancient balanced polymorphisms. Additionally, the greater divergence at silent sites ofone haplotype within each pair is suggestive of an origin through introgression.However, genetic diversity within haplotypes appears to be explained almost entirely byhaplotype frequencies, with higher frequencies associated with higher diversity.33Chapter 3Transcriptomic Characterization of TwoH. Annuus Haploblocks3.1 IntroductionLittle is known about the impact of SVs on the Helianthus transcriptome. However,recent comparisons of human and chimpanzee genomes suggest that SVs may introducelarge-scale deviations in gene expression by interfering with promoter regions near SVbreakpoints[66]. Understanding how gene expression varies between diverging SVhaplotypes could provide critical insight into the functional genetic differences betweenthe two lineages. Unfortunately, a major complication of studying haploblock-specificexpression in Helianthus is caused by a lack of haplotype-specific lines for any of the 37known haploblocks. Wild populations of Helianthus ssp contain substantial geneticvariability[15], further complicated by the fact that even closely related wild individualsrarely have uniform haplotypes of all SVs (Supplementary Methods: DEG in ArchivedTranscriptomes). All told, this makes detecting haplotype-specific differential geneexpression using wild samples nearly impossible. Thus, even in paired-sample studiesof highly similar wild individuals, significant noise is expected to be introduced bypolymorphism.34Despite these challenges, it is still possible to partially query differential expressioncaused by some haploblocks. Two domestic lines of H. annuus, SAM004 and SAM208,are inversely homozygous for haplotypes of Ann.01.01 and Ann.05.01, and havedomestic haplotypes for all other known haploblocks[40]. These two lineages certainlyhave background-specific transcriptomic divergence unrelated to their SV haplotypes[25].However, if an enrichment of differentially expressed genes (DEGs) can be foundspecifically within the haploblocks – which are expected to be more divergent than therest of the genome – it is a strong indicator that the genes in that region are beingexpressed based on SV haplotype.Here, we use 48 control samples from the RNAseq data by Lee et al 2021[25]. Thesedata encompass 24 samples each from SAM004 and SAM208 of two tissues (root andleaf) by three ages (16, 24, and 30 days) by four biological replicates per condition.Though there is too much genetic variation between SAM004 and SAM208 to supposeall DEG in the genome are caused by haploblock differences, DEG within the two H.annuus haploblocks can be assumed to be haplotype-specific if transcriptomicdivergence in this region is stronger than the genomic background. The SAM004Ann.01.01 haplotype is common in South-Eastern Texas, while its Ann.05.01 haplotype iscommon in the Western United States. Conversely, the SAM208 haplotype of Ann.01.01is common across the United States except for Texas, and its Ann.05.01 haplotype iscommon in the central United States from North Dakota to the Gulf of Mexico[40].Ann.01.01 is a small SV with limited gene clustering, making any specificpredictions about its potential function more difficult. On the other hand, Ann.05.01contains six clusters of enriched, highly homologous genes in the Ha412v2.1 referenceannotation, the largest of which contains seven genes highly homologous to the A.thaliana lignin biosynthesis gene AT5G48930: quinate/shikimatep-hydroxycinnamoyltransferase (HCT). The expression level of this gene is expected toinfluence the biochemical composition of a plant by causing fluctuations in ligninand/or flavonol content[56] [20], which can in turn impact how well a plant can adapt to a35variety of biotic and abiotic stresses[61] [26]. I hypothesize that Ann.05.01 haplotypes willhave differential expression of genes in this cluster, and by extension, I hypothesize thatdifferent haplotypes of Ann.05.01 will have haplotype-specific flavonoid profiles.3.2 Materials and Methods3.2.1 DataRaw RNAseq FASTQ was taken from the 48 control samples of Lee et al 2021[25],encompassing 24 quadruplicated samples of leaf and root tissue at three ages from twogenetic backgrounds. Gene expression libraries for hormone response and tissuespecificity were taken from Badouin et al 2017[14].3.2.2 Transcriptome AlignmentRaw FASTQ were trimmed with Trimmomatic v.0.36[3] and checked for qualityusing FastQC v.0.11.8. Trimmed FASTQ were then aligned to the Ha412HOV2.1reference genome using STAR Aligner v.2.7.1a(https://github.com/alexdobin/STAR) twice: once excluding multi-mappedfragments, and again with fractional inclusion of multi-mapped fragments. Raw countswere generated with the FeatureCounts function of Subread v.1.6.4[62].3.2.3 Differential Gene ExpressionAll differentially expressed genes (DEGs) between the two SAM populations foreach Age/Tissue combination were extracted using a standard dispersionestimate-based EdgeR/Limma pipeline in R. To determine whether inverted genes weremore likely to be DE than non-inverted genes, FDR-corrected Fisher’s Exact Tests wereused to check if either inverted region for each Age/Tissue combination was enriched36with DEGs. Data availability: https://github.com/katlande/Haplotype_Transcriptomes/blob/main/Differential_Expression/DEG.md3.3 ResultsGenes in this chapter were extracted from the Ha412v2.1 reference annotation unlessotherwise stated.3.3.1 Patterns of Differentially Expressed GenesRaw FASTQ from Lee et al 2021[25] was aligned to the Ha412v2.1 reference genomeonce without multi-mapping fragments, and once with fractional inclusion ofmulti-mapping fragments. Despite the presence of many highly homologous geneswithin haploblocks, the different alignments were highly similar (Table 3.1), with >90%genome-wide overlap between all comparisons, and similar trends within bothhaploblocks of interest.Table 3.1: Single and Multi-mapping DEG overlap between SAM208 and SAM004SingleMapping OnlyMulti-Mapping OnlyBothAlignmentsAge(days) Locus Root Leaf Root Leaf Root LeafGenome 69 106 185 132 1831 174816 Ann.01.01 0 0 0 0 4 4Ann.05.01 0 1 4 1 39 31Genome 78 86 192 138 1788 138224 Ann.01.01 0 0 0 0 4 4Ann.05.01 0 1 7 1 41 32Genome 87 89 171 138 2039 133330 Ann.01.01 0 0 0 0 4 2Ann.05.01 0 1 5 2 39 27Number of DEG unique to each alignment and overlapping multi-mapping and single-mappingalignments to Ha412v2.1, separated by age/tissue combination and locus of origin (full genome,within Ann.01.01 haploblock only, within Ann.05.01 haploblock only).37Using FDR-corrected Fisher’s Exact Tests, it was determined that genes weredifferentially expressed by genetic background inside the Ann.05.01 haploblock at aconsistently higher rate than genes in the rest of the genome across all tissue and agecombinations. On the other hand, there was no evidence in any tissue or sample age thatDEGs were enriched within the Ann.01.01 haploblock (Table 3.2). Thus, while there is aconsistent, detectable signature of gene expression induced by the Ann.05.01 haplotype,no such signature was detectable in Ann.01.01. Henceforth, only genes inside theAnn.05.01 haploblock will be considered haplotype-specific DEG.Overall gene expression (RPKM) was not different inside either haploblockcompared to the rest of the genome (two-sided p>0.01 for all comparisons, FDR-corrected10,000x permutation tests), suggesting that these results are not simply an artifact causedby haploblocks having higher overall gene expression.Table 3.2: DEG Enrichment within Haploblocks by Age and TissueHaploblock Tissue Age p.Adj Multi-Mapping p.Adj Single-Mapping16 0.657 0.600Leaf 24 0.576 0.537Ann.01.01 30 0.779 0.76316 0.657 0.600Root 24 0.657 0.60030 0.679 0.64316 5.91e-03 4.80e-03Leaf 24 1.11e-04 1.02e-04Ann.05.01 30 1.27e-03 1.60e-0316 2.28e-05 1.02e-04Root 24 2.93e-07 3.79e-0530 6.40e-05 7.86e-04Genetic background specific differentially expressed gene enrichment within each haploblock,for each age x tissue comparison in both single and multi-mapping alignments. p.Adj = FDR-corrected Fisher’s Exact tests.Genes inside haploblocks that display background-specific differential expressionpatterns in at least one tissue-age combination were annotated with their Arabidopsisthaliana TAIR homologs in order to determine the putative functions of each gene.38Broadly, functions of the TAIR homologs of these DEGs in different haplotypes ofAnn.05.01 in roots and leaves are as follows.Overall, there were far more upregulated genes in the introgressed haplotype ofAnn.05.01 common to the Western United States (SAM004) compared to the haplotypein the Central United States (SAM208). SAM004 DE genes inside the Ann.05.01haploblock in both root and leaf tissue at at least one time-point were homologous toTAIR genes with a wide variety of functions, including: biosynthetic genes (malate,isoprenoid, nucleotide, and steroid biosynthesis), mismatch repair and kinetochoreassociated genes, developmental genes (phloem formation, brassinosteroid signalling,MIKC), and a heat-shock protein. In addition, DEGs in the roots of these plants hadupregulations of genes homologous to wound and abiotic stress response genes, as wellas genes that function in actin binding and root hair elongation. On the other hand,SAM208 DE genes inside the Ann.05.01 haploblock in both root and leaf tissue at at leastone time-point were homologous to known alpha-beta hydrolases andsecE/sec61-gamma ER protein translocase genes, as well as to the shoot/floral meristempatterning gene ultrapetala. A putative cytochrome P450 homolog was also upregulatedin SAM208 roots. Notably, multiple putative immune genes were upregulated in all butSAM208 leaves, and at least one gene from the of the cluster of 7 genes highlyhomologous to the Arabidopsis thaliana lignin biosynthesis enzyme HCT was upregulatedin all tissue/background combinations. A full list of DEGs between haploblocks isavailable at: (https://github.com/katlande/Haplotype_Transcriptomes/tree/main/Differential_Expression).In addition to the HCT homolog cluster, Ann.05.01 contains five other clusters ofenriched homologous genes (Table 3.3), three of which contain genes that aredifferentially expressed by Ann.05.01 haplotype in young root and/or leaf tissue.Moreover, the two clusters that lack DEG between Ann.05.01 haplotypes (2 histonegenes and 2 hydroxysteroid dehydrogenase genes) do not appear actively expressed ineither of the tested tissues at the three tested time-points.39Table 3.3: Highly Homologous Gene Clusters in Ann.05.01TAIR Homolog Genes withinHaploblockGenes outsideHaploblock p.Adj Putative FunctionAT5G48930 7 3 1.24e-12 HCT; flavonoidbiosynthesisAT2G20825 5 0 1.06e-10 ULTRAPETALA;developmental regulatorAT3G48460 2 1 1.54e-03GDSL-motifesterase/acyltransferase/lipaseAT3G47350 2 4 4.84e-03 HSD (hydroxysteroiddehydrogenase)AT4G40040/AT5G10980/AT4G400302 4/5 4.84e-03 HistoneAT5G51060 2 5 5.87-03 RHD2; roothair elongationClusters of highly homologous genes enriched in the Ann.05.01 haploblock with TAIR homologsand their putative functions (from TAIR annotations). p.Adj = FDR-corrected Fisher’s Exact tests.3.3.2 Lignin Content by Ann.05.01 HaplotypeTable 3.4: Contributions to HCT Expression by TissueTissue Genomic HCTFPKMAnn.05.01 HCTFPKMAnn.05.01 HCTContributionBract 18038.0 10223.0 56.7%Stamen 8231.0 3625.0 44.0%Leaf 1123.4 373.0 33.2%Stem 6571.0 2021.0 30.8%Ligule 16263.0 2967.0 18.2%Style 35770.0 4566.0 12.8%Pollen 105.0 12.0 11.4%Ovary 8855.8 926.8 10.5%Corolla 12715.0 1229.0 9.7%Root 4874.5 141.2 2.9%Percent of HCT expressed by tissue, genomically and within Chr05 haploblocks, using expressionlibraries from Badouin et al 2017[14].The largest cluster of highly homologous genes inside the Ann.05.01 haploblock,seven homologs of HCT (AT5G48930), displays a high level of differential expression by40Ann.05.01 haplotype across all tested tissues and ages. Between just the leaf and roottissue, 5/7 of these genes are DE by haplotype, even though these genes are expected tobe lowly expressed in root and leaf tissue compared to other tissues such as the bractand stamen (Table 3.4).Moreover, in data from the filtered Eugene annotation of the Ha412 referencegenome, all genes homologous to HCT in Ann.05.01 have at least one haplotype-specificcoding change, as do 7/9 of the gene variants in Pet.05.01 in both subspecies. Theseresults suggest the presence of differential flavonoid biosynthesis by haplotype in someor all of the haplotypes of these haploblocks. In addition, lignin and flavonoidbiosynthesis terms are highly divergent between haplotypes of the Chr05 SV in all threespecies (Figure 3.1). Genes related to lignin biosynthesis are also the single mostdivergent type of gene between SV haplotypes after controlling for the expected level ofbackground genomic divergence in each GO term (Table 2.3).Figure 3.1: Top 10 GO Terms by Total Grantham Distance Between Haplotype-specific GeneVariants in Ha412HOChr05 HaploblocksGO terms with the 10 largest total Grantham distances between alternate haplotypes in all threeHa412H0Chr05 SVs, extracted from GO data in Chapter 1. Green terms are directly associated toflavinoid biosynthesis.Phloroglucinol stains of wild H. annuus petiole cross-sections were conducted tofind evidence of haplotype-specific lignification, but evidence was inconclusive41(Supplementary Figure 4). This may be due to high phenotypic variability in wildpopulations, or a lack of differential lignification in petiole tissue specifically.3.4 Discussion3.4.1 Haplotype-Specific Transcriptomic DifferencesHaplotype-specific transcriptional differences in Ann.05.01 are unlikely to be foundexclusively in genes with coding sequences within the SV, as DNA-templated regulationof transcription is the gene function predicted to be most divergent between Ann.05.01haplotypes and transcription factors can act across the entire genome[35]. Likely, themajority of haplotype-specific DEG were excluded by this study, and haploblock-specificRILs would be needed to understand the full scope of the transcriptional divergencebetween haplotypes.Nonetheless, the functions of the DEG that were detectable were in line with thethose of genes with high haplotype-specific chemical divergence, such as those involvedin lignin and flavonoid biosynthesis, lipid metabolism, meristem phase transition, andimmune processes.3.4.2 HCT and Lignin Biosynthesis in Chr05 HaploblocksOf particular note is the Ann.05.01-specific differential expression of a cluster offive genes homologous to HCT. HCT is a crucial enzyme in lignin biosynthesis, and itsexpression level is intricately related to the balance of lignin:flavonols produced by aplant’s flavonoid biosynthetic pathway[20].Flavonoid biosynthesis is a highly conserved pathway in plants, its originspredating the last common ancestor of cyanobacteria and vascular plants[28]. Across theentire plant kingdom, it is responsible for the production of thousands uniquemetabolites[28] that play roles in a wide range of biological processes. In Arabidopsis42thaliana, it has been demonstrated that silencing the expression of HCT results indecreased lignin content and increased flavonol content[56] Moreover, in other species,HCT loss of function individuals show similar lignin-depleted phenotypes[16] [5] [26].Notably, increasing the content of either lignin or flavonols in a plant is expected toimpact the plant’s phenotype quite substantially. For example, plants with decreasedlignin content tend to grow more slowly and flower later[56] [45], and if lignin depletion issevere enough it may even cause male sterility[23] or decreased seed germination[37].Lignin is also an important compound for helping plants adapt to temperature, osmotic,and herbivory stress, as well as playing an important role in basal immuneresponse[24] [20] [61]. Conversely, flavonols are important for protecting plants from UVdamage, producing pigments for pollinator guidance, forming root nodules withsymbiotic bacteria, mediating plant interactions with symbiotic fungi, and more[43] [4].Thus, it stands to reason that haplotype-specific alterations to HCT – and by extension tothe balance of flavonols and lignins in the plant – would make the haplotypes moreadaptable to disparate environments.HCT homologs remain a top candidate for the origin of haplotype-specificphenotypes in the Chr05 SVs in Helianthus, as lignin biosynthetic genes have strongtranscriptional divergence in Ann.05.01, high chemical divergence in their codingsequences in all three Chr05 SVs, and this SV is known to be associated with floweringtime in H. petiolaris ssp. fallax and temperature in H. petiolaris petiolaris [40].From cursory Wesiner stains, it is known that both the distribution and density oflignin in the petioles of wild H. annuus individuals are extremely variable, even betweenclosely related samples of the same Ann.05.01 haplotype. This is not unexpected, asgenes belonging to the flavonoid biosynthesis pathway can be found throughout thegenome, including within haploblocks other than Ann.05.01. Testing the effect that thehaplotype-specific divergence of the Chr05 haploblock HCT homologs have on ligninbiosynthesis would require more in-depth methods, and may even necessitate the use ofSV-specific inbred lines that do not exist at present.433.5 ConclusionOverall, there are demonstrable differences in the gene expression of alternateAnn.05.01 haplotypes. Signals of haplotype-specific DEG are even strong enough to cutthrough the substantial noise generated by comparing two lineages with highly distincttranscriptomic profiles. Further, the functions of haplotype-specific DE genes fall in linewith the functions that would be expected given known trends in haplotype-specificCDS divergence.Likely, the majority of Ann.05.01 haplotype-specific gene expression variationremains uncovered in the rest of the genome. Still, this data strongly suggests thatalterations to the lignin biosynthetic pathway are driving divergence and localadaptation in alternate haplotypes of the Ha412HOChr05 SVs in H. annuus and H.petiolaris ssp. More broadly, this data confirms the expectation that alternate haplotypesof Helianthus SVs have highly unique transcriptomic profiles, and suggests that futuretranscriptomic studies of other SVs are likely to be fruitful and insightful.44Chapter 4Concluding ChapterIn this thesis, I uncovered and characterized the genomic differences betweenhaplotypes of structural variants (SVs) in Helianthus. Given previous evidence that theseSVs are often fundamentally involved in ecotypic adaptation[40] [21], I hypothesized thatgenes related to environmental stress and/or locally advantageous phenotypes wouldbe substantially divergent in a haplotype-specific manner. This was broadly confirmedwith respect to sequence divergence, differential expression, and signals of directionalselection. In addition, my results showed that haplotypes of these SVs have highlydistinct population genetic profiles. Altogether, these findings illuminate the origins ofthese SVs and the evolutionary history of the genus Helianthus as a whole.Despite these promising results, this thesis only looks at genetic variationintroduced by biallelic SNPs in protein-coding sequences. Therefore, any divergenceintroduced by insertions and deletions, as well as mutations of non-coding regions,remain to be thoroughly explored. On top of this, the tests I used to identify the selectiveforces acting in these regions were underpowered due to short the phylogeneticdistances between haplotypes. This is evident in the fact that results from two similartests were in disagreement about the type of selection acting on 41 genes. 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The methods and results from these additionalexperiments are reported on below.Appendix A: Supplementary MethodsGreenhouse TrialsSeeds of wild H. annuus individuals from 6 populations polymorphic for fourprecipitation-associated inversions, Ann01.01, Ann13.01, Ann13.02, and Ann14.01, weregrown to seedlings in jiffy-pots on the lab bench. Once seedlings were approximatelytwo weeks old, 90 of the healthiest individuals were repotted in cones and transferred tothe Horticulture Greenhouse at the University of British Columbia, Vancouver.Individuals were grown to maturity, keeping track of flowering/budding time,growth metrics, and measuring drought stress phenotypes of mature individualsincluding survival days without water, final dry root mass, and leaf proline contentunder drought stress.CAPS MarkersCAPS markers for each SV were generated by identifying SNPs that segregate withone SV haplotype with high fidelity and induce a restriction site. 15-25bp long primerswere constructed around each candidate SNP, and the accuracy of each candidate primer54set was tested using purified DNA from samples of known haplotypes (SupplementaryTable 2).Proline Content AssayProline content was determined using isatin paper staining as described inA´braha´m et al 2010[67]. Samples were young leaves were taken from plants at peakdrought stress, flash frozen, ground to a fine powder, and blotted onto isatin paper.Proline content was determined colorimetrically by comparing the mean grey area ofdots in imageJ against an L-proline standard.Lignin StainingPaired wild H. annuus samples with alternate haplotypes of Ann.05.01 wereselected in order to minimize genetic deviation between samples (Supplementary Table4). Dry petiole specimens were rehydrated in diH2O overnight, then cut into sections byhand. Weisner staining was conducted on three technical replicates of each samplefollowing the concentrations as described in Mitra and Loque´ 2014[50]. Each sample wasstained and photographed in triplicate; the most representative image was used for eachsample. Lignification was quantified as the percent of stained cross-sectional area,counted with imageJ. Significance was determined with a paired-sample t-test.DEG in Archived TranscriptomesData: Raw FASTQ for 56 wild H. annuus, H. argophyllus, and H. petiolaristranscriptomes originally sequenced by Moyers and Rieseberg 2013[7] were extracted.Haplotyping SVs: Raw FASTQ were trimmed, checked, and aligned to theHanXRQv1 reference genome using the Star 2-Pass Alignment protocol for RNAseq datain star/2.7.1a. Variants were called and filtered from the resulting BAM files using theRieseberg Lab Reproducible Variant Calling pipeline(https://www.github.com/rieseberglab/snp-calling). Known diagnostic55SNPs for all inversions were then extracted and used to determine the most likely SVhaplotypes for all Helianthus inversions in each sample using a custom Python/2.7Haplotyping pipeline (github.com/katlande/Helianthus_VCF_Haplotyping).To identify which samples had been reliably haplotyped versus those which had beenfalsely assigned a haplotype, a simulation was run to determine haplotype accuracy forsamples haplotyped with differing numbers of diagnostic SNPs. Only reliablyhaplotyped individuals were used for haplotype-specific DE analysis.Differential Expression by Haplotype: Trimmed FASTQ were again aligned, thistime to the Ha412v2 reference genome, and count matrices were generated. DE analysiswas conducted in R with a standard EdgeR/Limma pipeline. Due to exorbitantly highlevels of noise, no haplotype-specific DEG could be determined.56Appendix B: Supplementary TablesSupplementary Table 1Gene Count Sample SizeHaploblock Chromosome Loci (mb) Ha412v2.1 FilteredEugeneHaplotype0Haplotype2Ann.01.01 Ha412HOChr01 6.2-9.7 107 93 425 90Ann.05.01 Ha412HOChr05 148.2-177.4 480 568 265 134Ann.11.01 Ha412HOChr11 19.4-54.0 630 635 464 38Ann.13.01 Ha412HOChr13 8.6-109.5 1819 1547 245 201Ann.15.01 Ha412HOChr15 103.8-176.6 1209 938 245 183Arg.06.01 Ha412HOChr06 153.6-154.2,153.6-155.1,161.2-190.7 21 261 265 11Arg.10.01 Ha412HOChr10 161.2-190.7 599 914 222 38PetF.05.01 Ha412HOChr05 154.5-181.0,182.1-185.7 536 691 15 227PetF.09.01 Ha412HOChr09 105.3-122.6,128.9-140.6 671 556 205 32PetF.11.01 Ha412HOChr011 3.6-65.7 1151 1282 44 191PetF.14.01 Ha412HOChr14 101.7-171.1 1510 1586 26 222PetF.17.01 Ha412HOChr17 12.4-22.5 287 368 84 145PetP.05.01 Ha412HOChr05 156.8-179.9,182.1-185.8 536 634 37 76PetP.09.01 Ha412HOChr09 105.3-123.5,128.8-140.9 671 565 78 30PetP.11.01 Ha412HOChr11 3.3-65.7 1151 1287 74 36PetP.17.01 Ha412HOChr17 11.7-22.6 287 392 124 11Sample data for Haploblocks. Total species samples: H. annuus, 720; H. argophyllus, 299; H. petio-laris ssp. fallax, 259; H. petiolaris ssp. petiolaris, 168.Supplementary Table 2Haploblock SamplePrediction (%) EnzymeUncuthaplotypeFwdsequenceRevsequenceUncutlength (bp)Cutlength (bp)ann.01.01 97.50 MluCI Hap 0 GCAACTGTTTGGTCGTCTGT CCTTGTTTATTGGTCTTTGGG 344 85, 259ann.01.01 100.00 HpyCH4IV Hap 0 GGAGTGTGCAATAATGCTG CCGGTAGATGTTAGGTTTTCC 395 210, 185ann.01.01 87.18 Hpy166II Hap 2 CCTCTAAACCCTAGCACC GAAACTAGATGTGGTCACAG 403 225, 278ann.13.01 87.10 TseI Hap 0 GCTTGCAATTTGCGTTTGC GCGTCGGATGCTATTCGTATC 375 151, 224ann.13.01 100.00 MluCI Hap 0 GCAGTGTCTTCTTGCGTC CCAATGAACCACTCGAAAAC 283 208, 75ann.13.01 100.00 Hpy188I Hap 2 GCAGTGTCTTCTTGCGTC CCAATGAACCACTCGAAAAC 327 174, 153ann.13.02 100.00 HpyCH4IV Hap 0 CACACAGAGCAGGGATAA GTGACTTTAGTGGAACACCT 317 181, 136ann.13.02 92.31 PleI Hap 2 GCAATGGTTAAATCACTTCC GCCGTGACTCAAAAAATGA 281 149, 132ann.13.02 96.77 ApoI Hap 2 TCCAGCATTGTCGTTGG GGTTCAAAGGAAGACCGA 479 193, 286ann.14.01 90.32 BstUI Hap 2 TGGTGGTGAGTTATAGAAGG GATGCATAGAGAGACACATT 536 275, 261ann.14.01 93.10 BsmAI Hap 0 GGGAGGCTAAAACACATTAG ATGCATCTCTTGTTGGACTC 412 200, 212ann.14.01 93.33 HpyCH4IV Hap 2 GGCAAAGGTAGTTGAATTGAC ACATGTAAAACAGGTTGTGC 316 137, 179ann.14.01 86.21 HpyCH4IV Hap 2 CGGGCATCAAACTCAAA CATGTCACATTGTCAAGAGA 338 195, 143CAPS primers for H. annuus Haploblocks. CAPS primer sets used in drought trial plants todetermine SV haplotypes.57Supplementary Table 3Haploblock Stop CodonAlterations Notable FunctionsGenes withHomologANN.01.01 0 NA NAANN.05.01 3 None 0/3ANN.11.01 11 3 immune genes1 dsRNABP 5/11ANN.13.01 13 1 heatshock domain1 flowering time 6/13ANN.15.01 7 2 auxin signalling1 pistil development 3/7ARG.06.01 3 None 2/3ARG.10.01 9 1 RNA pol1 nitrate transporter 5/9PETFAL.05.01 6 None 4/6PETFAL.09.01 71 JA signalling1 Ca2+ uptake1 root mechanical sensing2/7PETFAL.11.01 5 1 immune1 GA signalling 2/5PETFAL.14.01 9 1 phosphorus stavation1 editosome protein 2/9PETFAL.17.01 2 1 Agamous-related TF 0/2PETPET.05.01 3 None 0/3PETPET.09.01 6 None 4/6PETPET.11.01 61 GA signalling1 Reverse transcriptase1 immune1/6PETPET.17.01 2 1 Agamous-related TF 0/2Genes with haplotype-specific stop codon alterations in the Ha412 filtered Eugene annotation.58Supplementary Table 4SourcePopulation Haplotype 0 Haplotype 2 Chr SV Divergent SVsANN.10 ANN0894 ANN0893 0 0 NoneANN.10 ANN0896 ANN0899 0 0 NoneANN.27 ANN1069 ANN1068 0 0 NoneANN.58 ANN1372 ANN1373 0 0 NoneANN.67 HT211.MO1W-39 HT142.MO1W-15 0 0 NoneANN.02 ANN0811 ANN0818 0.5 1 Ann.15.01ANN.09 ANN0882 ANN0881 0.5 1 Ann.13.01ANN.20 ANN0994 ANN0993 0.5 1 Ann.16.02ANN.20 ANN1000 ANN0991 0.5 1 Ann.11.01ANN.25 ANN1041 ANN1044 0.5 1 Ann.11.01ANN.27 ANN1061 ANN1065 0.5 1 Ann.13.01ANN.32 ANN1114 ANN1115 0.5 1 Ann.11.01ANN.52 ANN1314 ANN1315 0.5 1 Ann.14.01ANN.57 ANN1365 ANN1366 0.5 1 Ann.01.01ANN.58 ANN1378 ANN1374 0.5 1 Ann.16.01ANN.61 ANN1406 ANN1403 0.5 1 Ann.16.01ANN.66 HT231.MB1W-8 HT233.MB1W-14 0.5 1 Ann.11.01ANN.68 HT44.ND1W-12 HT213.ND1W-20 0.5 1 Ann.17.01ANN.11 ANN0906 ANN0902 1 2 Ann.16.01, Ann.16.02ANN.12 ANN0911 ANN0912 1 2 Ann.14.01, Ann.17.01ANN.21 ANN1006 ANN1007 1 1 Ann.16.01ANN.42 ANN1213 ANN1218 1 2 Ann.13.02, Ann.15.01ANN.43 ANN1226 ANN1223 1 2 Ann.01.01, Ann.16.01ANN.51 ANN1306 ANN1310 1 2 Ann.11.01, Ann.17.01ANN.70 HT219.SD2W-38 HT013.SD2W-18 1 2 Ann.01.01, Ann.14.01ANN.12 ANN0920 ANN0914 1 2 Ann.13.01, Ann.16.01ANN.25 ANN1047 ANN1045 1 2 Ann.11.01, Ann.15.01ANN.58 ANN1377 ANN1379 1 2 Ann.14.01, Ann.14.02ANN.16 ANN0957 ANN0951 1.5 3 Ann.14.01, Ann.15.01, Ann.17.01ANN.16 ANN0958 ANN0955 1.5 2 Ann.15.01, Ann.17.01ANN.19 ANN0981 ANN0985 1.5 3 Ann.14.01, Ann.15.01, Ann.16.02ANN.19 ANN0982 ANN0988 1.5 2 Ann.13.01, Ann.13.02ANN.35 ANN1142 ANN1147 1.5 3 Ann.13.01, Ann.15.01, Ann.17.01ANN.36 ANN1153 ANN1154 1.5 3 Ann.13.01, Ann.13.02, Ann.16.01ANN.42 ANN1211 ANN1212 1.5 3 Ann.01.01, Ann.14.01, Ann.16.01ANN.44 ANN1233 ANN1238 1.5 3 Ann.14.01, Ann.14.02, Ann.16.01ANN.44 ANN1237 ANN1239 1.5 3 Ann.14.01, Ann.14.02, Ann.16.01ANN.53 ANN1328 ANN1322 1.5 3 Ann.11.01, Ann.15.01, Ann.16.02ANN.66 HT125.MB1W-20 HT234.MB1W-39 1.5 3 Ann.11.01, Ann.14.01, Ann.17.01ANN.20 ANN0998 ANN0992 1.5 3 Ann.11.01, Ann.13.01, Ann.16.01ANN.42 ANN1214 ANN1220 1.5 2 Ann.01.01, Ann.13.01ANN.52 ANN1311 ANN1313 2 4 Ann.13.01, Ann.14.01, Ann.15.01, Ann.16.02ANN.65 HT228.KS2W-12 HT227.KS2W-9 2 4 Ann.13.01, Ann.13.02, Ann.15.01, Ann.16.01ANN.70 HT170.SD2W-14 HT217.SD2W-21 2 4 Ann.01.01, Ann.13.01, Ann.13.02, Ann.14.01ANN.18 ANN0978 ANN0974 2.5 5 Ann.01.01, Ann.13.01, Ann.14.01, Ann.15.01, Ann.16.01ANN.51 ANN1307 ANN1308 2.5 4 Ann.11.01, Ann.16.01, Ann.16.02, Ann.17.01ANN.53 ANN1324 ANN1325 2.5 4 Ann.13.01, Ann.13.02, Ann.14.01, Ann.15.01ANN.41 ANN1209 ANN1201 3 6 Ann.01.01, Ann.13.01, Ann.13.02, Ann.14.01, Ann.14.02, Ann.15.01ANN.18 ANN0979 ANN0971 4 6 Ann.13.01, Ann.13.02, Ann.14.02, Ann.15.01, Ann.16.01, Ann.17.01ANN.65 ANN1410 ANN1439 4.5 7 Ann.01.01, Ann.11.01, Ann.13.01, Ann.13.02, Ann.14.01, Ann.14.02, Ann.15.01Wild sample pairs chosen for petiole staining with alternate haplotypes of Ann.05.01. Within-population pairs with the fewest possible numbers of divergent SVs were chosen to reduce geneticvariability. Chr: number of chromosomes with divergent haplotype between samples, SV: numberof SVs with divergent haplotype between samples. Some samples discarded during experimenta-tion due to low quality tissue.59Appendix C: Supplementary FiguresSupplementary Figure 1: Drought Tolerance versus Haplotype in Wild Populations of H. annuusfor Four HaploblocksANN18 ANN36 ANN40 ANN45 ANN56 ANN600 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 20123HaplotypeDays to 50% WiltedANN18 ANN36 ANN40 ANN45 ANN56 ANN600 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 20123HaplotypeDays to 50% WiltedANN18 ANN36 ANN40 ANN45 ANN56 ANN600 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 20123HaplotypeDays to 50% WiltedANN18 ANN36 ANN40 ANN45 ANN56 ANN600 1 2 0 1 2 0 1 2 0 1 2 0 1 2 0 1 20123HaplotypeDays to 50% WiltedNo significant trends (p0.05 were detectable for any measured metrics of drought tolerance. Met-rics included: Days to 50% wilted leaves under drought stress (shown), Proline content of youngleaves under drought stress, days to budding and flowering, total plant height, and dry root mass.Haploblocks: Ann.01.01 (Top left), Ann.13.01 (Top right), Ann.13.02 (Bottom left) Ann.14.01 (Bot-tom right).60Supplementary Figure 2: Haplotype-Specific Grantham Distances of Enriched and non-EnrichedGO Terms in Helianthus HaploblocksPETPET_05_01 PETPET_09_01 PETPET_11_01 PETPET_17_01PETFAL_09_01 PETFAL_11_01 PETFAL_14_01 PETFAL_17_01ANN_15_01 ARG_06_01 ARG_10_01 PETFAL_05_01ANN_01_01 ANN_05_01 ANN_11_01 ANN_13_0110 100 1000 10000 10 100 1000 10000 10 100 1000 10000 10 100 1000 1000001234012340123401234Grantham ValueFrequencyEnrichedNon−EnrichedHaploblock Enriched vs. Non−Enriched GO TermsChemical Distance by GO termMean summed Grantham values of haploblock-enriched GO terms were larger in all haploblocksexcept Ann.13.01 and Petfal.17.01, but differences lack statistical power. Only Ann.11.01 had astatistically significant p-value: enriched GO terms mean Grantham distance 205.7, non-enrichedterms mean Grantham distance: 96.0, t-test p-value” 1.42e-06.61Supplementary Figure 3: Phloroglucinol stains of rehydrated wild H. annuus petioles.Haplotype 0 Haplotype 2Ph-HCl EtOH Ph-HCl EtOH DataPop = Ann.02Hap0 = Ann0811,% red area = 0.544Hap2 = Ann0818,% red area = 0.274Pop = Ann.09Hap0 = Ann0882,% red area = 0.459Hap2 = Ann0881,% red area = 0.370Pop = Ann.10Hap0 = Ann0894,% red area = 0.215Hap2 = Ann0893,% red area = 0.104Pop = Ann.10Hap0 = Ann0896,% red area = 0.347Hap2 = Ann0899,% red area = 0.115Pop = Ann.11Hap0 = Ann0906,% red area = 0.110Hap2 = Ann0902,% red area = 0.085Pop = Ann.12Hap0 = Ann0911,% red area = 0.583Hap2 = Ann0912,% red area = 0.5331A selection of paired Phl-HCl stains, total n=32 pairs. Paired samples of alternate haplotypeswere drawn from wild populations. Stain intensity and area were quantified in ImageJ, but nodefinitive divergence in either metric was distinguishable based on haplotype.62
Thesis/Dissertation
eng
Genome Science and Technology
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Rieseberg, Loren H.
Genomic characterization of divergent haplotypes of large structural variants in the genus Helianthus
Text