Complex Polyploids: Origins, Genomic Composition, and Role of Introgressed Alleles.

Introgression allows polyploid species to acquire new genomic content from diploid progenitors or from other unrelated diploid or polyploid lineages, contributing to genetic diversity and facilitating adaptive allele discovery. In some cases, high levels of introgression elicit the replacement of large numbers of alleles inherited from the polyploid's ancestral species, profoundly reshaping the polyploid's genomic composition. In such complex polyploids it is often difficult to determine which taxa were the progenitor species and which taxa provided additional introgressive blocks through subsequent hybridization. Here, we use population-level genomic data to reconstruct the phylogenetic history of Betula pubescens (downy birch), a tetraploid species often assumed to be of allopolyploid origin and which is known to hybridize with at least four other birch species. This was achieved by modeling of polyploidization and introgression events under the multispecies coalescent and then using an approximate Bayesian computation (ABC) rejection algorithm to evaluate and compare competing polyploidization models. We provide evidence that B. pubescens is the outcome of an autoploid genome doubling event in the common ancestor of B. pendula and its extant sister species, B. platyphylla, that took place approximately 178,000-188,000 generations ago. Extensive hybridization with B. pendula, B. nana, and B. humilis followed in the aftermath of autopolyploidization, with the relative contribution of each of these species to the B. pubescens genome varying markedly across the species' range. Functional analysis of B. pubescens loci containing alleles introgressed from B. nana identified multiple genes involved in climate adaptation, while loci containing alleles derived from B. humilis revealed several genes involved in the regulation of meiotic stability and pollen viability in plant species.

Early-acting inbreeding depression can evolve as an inbreeding avoidance mechanism.

Despite the potential for mechanical, developmental and/or chemical mechanisms to prevent self-fertilization, incidental self-fertilization is inevitable in many predominantly outcrossing species. In such cases, inbreeding can compromise individual fitness. Unquestionably, much of this inbreeding depression is maladaptive. However, we show that when reproductive compensation allows for the replacement of inviable embryos lost early in development, selection can favour deleterious recessive variants that induce 'self-sacrificial' death of inbred embryos. Our theoretical results provide numerous testable predictions which could challenge the assumption that inbreeding depression is always maladaptive. Our work is applicable any species that cannot fully avoid inbreeding, exhibits substantial inbreeding depression, and has the potential to compensate embryos lost early in development. In addition to its general applicability, our theory suggests that self-sacrificial variants might be responsible for the remarkably low realized selfing rates of gymnosperms with high primary selfing rates, as gymnosperms exhibit strong inbreeding depression, have effective reproductive compensation mechanisms, and cannot evolve chemical self-incompatibility.

BELMM: Bayesian model selection and random walk smoothing in time-series clustering.

MOTIVATION: Due to advances in measuring technology, many new phenotype, gene expression, and other omics time-course datasets are now commonly available. Cluster analysis may provide useful information about the structure of such data. RESULTS: In this work, we propose BELMM (Bayesian Estimation of Latent Mixture Models): a flexible framework for analysing, clustering, and modelling time-series data in a Bayesian setting. The framework is built on mixture modelling: first, the mean curves of the mixture components are assumed to follow random walk smoothing priors. Second, we choose the most plausible model and the number of mixture components using the Reversible-jump Markov chain Monte Carlo. Last, we assign the individual time series into clusters based on the similarity to the cluster-specific trend curves determined by the latent random walk processes. We demonstrate the use of fast and slow implementations of our approach on both simulated and real time-series data using widely available software R, Stan, and CU-MSDSp. AVAILABILITY AND IMPLEMENTATION: The French mortality dataset is available at http://www.mortality.org, the Drosophila melanogaster embryogenesis gene expression data at https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE121160. Details on our simulated datasets are available in the Supplementary Material, and R scripts and a detailed tutorial on GitHub at https://github.com/ollisa/BELMM. The software CU-MSDSp is available on GitHub at https://github.com/jtchavisIII/CU-MSDSp.

Between but Not Within-Species Variation in the Distribution of Fitness Effects.

New mutations provide the raw material for evolution and adaptation. The distribution of fitness effects (DFE) describes the spectrum of effects of new mutations that can occur along a genome, and is, therefore, of vital interest in evolutionary biology. Recent work has uncovered striking similarities in the DFE between closely related species, prompting us to ask whether there is variation in the DFE among populations of the same species, or among species with different degrees of divergence, that is whether there is variation in the DFE at different levels of evolution. Using exome capture data from six tree species sampled across Europe we characterized the DFE for multiple species, and for each species, multiple populations, and investigated the factors potentially influencing the DFE, such as demography, population divergence, and genetic background. We find statistical support for the presence of variation in the DFE at the species level, even among relatively closely related species. However, we find very little difference at the population level, suggesting that differences in the DFE are primarily driven by deep features of species biology, and those evolutionarily recent events, such as demographic changes and local adaptation, have little impact.

Strong Purifying Selection in Haploid Tissue-Specific Genes of Scots Pine Supports the Masking Theory.

The masking theory states that genes expressed in a haploid stage will be under more efficient selection. In contrast, selection will be less efficient in genes expressed in a diploid stage, where the fitness effects of recessive deleterious or beneficial mutations can be hidden from selection in heterozygous form. This difference can influence several evolutionary processes such as the maintenance of genetic variation, adaptation rate, and genetic load. Masking theory expectations have been confirmed in single-cell haploid and diploid organisms. However, in multicellular organisms, such as plants, the effects of haploid selection are not clear-cut. In plants, the great majority of studies indicating haploid selection have been carried out using male haploid tissues in angiosperms. Hence, evidence in these systems is confounded with the effects of sexual selection and intraspecific competition. Evidence from other plant groups is scarce, and results show no support for the masking theory. Here, we have used a gymnosperm Scots pine megagametophyte, a maternally derived seed haploid tissue, and four diploid tissues to test the strength of purifying selection on a set of genes with tissue-specific expression. By using targeted resequencing data of those genes, we obtained estimates of genetic diversity, the site frequency spectrum of 0-fold and 4-fold sites, and inferred the distribution of fitness effects of new mutations in haploid and diploid tissue-specific genes. Our results show that purifying selection is stronger for tissue-specific genes expressed in the haploid megagametophyte tissue and that this signal of strong selection is not an artifact driven by high expression levels.

Reproductive Compensation and Selection among Viable Embryos Drive the Evolution of Polyembryony.

AbstractSimple polyembryony, where one gametophyte produces multiple embryos with different sires but the same maternal haplotype, is common among vascular plants. We develop an infinite-sites, forward population genetics model showing that together polyembryony's two benefits-"reproductive compensation" achieved by providing a backup for inviable embryos and the opportunity to favor the fitter of surviving embryos-can favor its evolution. Our model tests how these factors can favor the evolution of polyembryony and how these underlying benefits of polyembryony shape the genetic load under a range of biological parameters. While these two benefits are difficult to disentangle in nature, we construct variant models of polyembryony that either only include or only exclude the opportunity for reproductive compensation. We find that reproductive compensation strongly favors the evolution of polyembryony and that polyembryony is favored much more weekly in its absence, suggesting that the benefit of a backup embryo is the major force favoring polyembryony. Remarkably, we find nearly identical results in cases in which mutations impact either embryonic or postembryonic fitness (no pleiotropy) and in cases in which mutations have identical effects on embryonic and postembryonic fitness (extreme pleiotropy). Finally, we find that the consequences of polyembryony depend on its function-polyembryony results in a decrease in mean embryonic fitness when acting as a mechanism of embryo compensation and ultimately increases mean embryonic fitness when we exclude this potential benefit.

Genomics and adaptation in forest ecosystems.

Rapid human-induced environmental changes like climate warming represent a challenge for forest ecosystems. Due to their biological complexity and the long generation time of their keystone tree species, genetic adaptation in these ecosystems might not be fast enough to keep track with conditions changing at such a fast pace. The study of adaptation to environmental change and its genetic mechanisms is therefore key for ensuring a sustainable support and management of forests. The 4-day conference of the European Research Group EvolTree (https://www.evoltree.eu) on the topic of "Genomics and Adaptation in Forest Ecosystems" brought together over 130 scientists to present and discuss the latest developments and findings in forest evolutionary research. Genomic studies in forest trees have long been hampered by the lack of high-quality genomics resources and affordable genotyping methods. This has dramatically changed in the last few years; the conference impressively showed how such tools are now being applied to study past demography, adaptation and interactions with associated organisms. Moreover, genomic studies are now finally also entering the world of conservation and forest management, for example by measuring the value or cost of interspecific hybridization and introgression, assessing the vulnerability of species and populations to future change, or accurately delineating evolutionary significant units. The newly launched conference series of EvolTree will hopefully play a key role in the exchange and synthesis of such important investigations. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11295-022-01542-1.

Taming the massive genome of Scots pine with PiSy50k, a new genotyping array for conifer research.

Pinus sylvestris (Scots pine) is the most widespread coniferous tree in the boreal forests of Eurasia, with major economic and ecological importance. However, its large and repetitive genome presents a challenge for conducting genome-wide analyses such as association studies, genetic mapping and genomic selection. We present a new 50K single-nucleotide polymorphism (SNP) genotyping array for Scots pine research, breeding and other applications. To select the SNP set, we first genotyped 480 Scots pine samples on a 407 540 SNP screening array and identified 47 712 high-quality SNPs for the final array (called 'PiSy50k'). Here, we provide details of the design and testing, as well as allele frequency estimates from the discovery panel, functional annotation, tissue-specific expression patterns and expression level information for the SNPs or corresponding genes, when available. We validated the performance of the PiSy50k array using samples from Finland and Scotland. Overall, 39 678 (83.2%) SNPs showed low error rates (mean = 0.9%). Relatedness estimates based on array genotypes were consistent with the expected pedigrees, and the level of Mendelian error was negligible. In addition, array genotypes successfully discriminate between Scots pine populations of Finnish and Scottish origins. The PiSy50k SNP array will be a valuable tool for a wide variety of future genetic studies and forestry applications.

Atlas of tissue-specific and tissue-preferential gene expression in ecologically and economically significant conifer Pinus sylvestris.

Despite their ecological and economical importance, conifers genomic resources are limited, mainly due to the large size and complexity of their genomes. Additionally, the available genomic resources lack complete structural and functional annotation. Transcriptomic resources have been commonly used to compensate for these deficiencies, though for most conifer species they are limited to a small number of tissues, or capture only a fraction of the genes present in the genome. Here we provide an atlas of gene expression patterns for conifer Pinus sylvestris across five tissues: embryo, megagametophyte, needle, phloem and vegetative bud. We used a wide range of tissues and focused our analyses on the expression profiles of genes at tissue level. We provide comprehensive information of the per-tissue normalized expression level, indication of tissue preferential upregulation and tissue-specificity of expression. We identified a total of 48,001 tissue preferentially upregulated and tissue specifically expressed genes, of which 28% have annotation in the Swiss-Prot database. Even though most of the putative genes identified do not have functional information in current biological databases, the tissue-specific patterns discovered provide valuable information about their potential functions for further studies, as for example in the areas of plant physiology, population genetics and genomics in general. As we provide information on tissue specificity at both diploid and haploid life stages, our data will also contribute to the understanding of evolutionary rates of different tissue types and ploidy levels.

Adaptive responses to temperature and precipitation variation at the early-life stages of Pinus sylvestris.

Early-stage fitness variation has been seldom evaluated at broad scales in forest tree species, despite the long tradition of studying climate-driven intraspecific genetic variation. In this study, we evaluated the role of climate in driving patterns of population differentiation at early-life stages in Pinus sylvestris and explored the fitness and growth consequences of seed transfer within the species range. We monitored seedling emergence, survival and growth over a 2-yr period in a multi-site common garden experiment which included 18 European populations and spanned 25° in latitude and 1700 m in elevation. Climate-fitness functions showed that populations exhibited higher seedling survival and growth at temperatures similar to their home environment, which is consistent with local adaptation. Northern populations experienced lower survival and growth at warmer sites, contrary to previous studies on later life stages. Seed mass was higher in populations from warmer areas and was positively associated with survival and growth at more southern sites. Finally, we did not detect a survival-growth trade-off; on the contrary, bigger seedlings exhibited higher survival probabilities under most climatic conditions. In conclusion, our results reveal that contrasting temperature regimes have played an important role in driving the divergent evolution of P. sylvestris populations at early-life stages.

Model guided trait-specific co-expression network estimation as a new perspective for identifying molecular interactions and pathways.

A wide variety of 1) parametric regression models and 2) co-expression networks have been developed for finding gene-by-gene interactions underlying complex traits from expression data. While both methodological schemes have their own well-known benefits, little is known about their synergistic potential. Our study introduces their methodological fusion that cross-exploits the strengths of individual approaches via a built-in information-sharing mechanism. This fusion is theoretically based on certain trait-conditioned dependency patterns between two genes depending on their role in the underlying parametric model. Resulting trait-specific co-expression network estimation method 1) serves to enhance the interpretation of biological networks in a parametric sense, and 2) exploits the underlying parametric model itself in the estimation process. To also account for the substantial amount of intrinsic noise and collinearities, often entailed by expression data, a tailored co-expression measure is introduced along with this framework to alleviate related computational problems. A remarkable advance over the reference methods in simulated scenarios substantiate the method's high-efficiency. As proof-of-concept, this synergistic approach is successfully applied in survival analysis, with acute myeloid leukemia data, further highlighting the framework's versatility and broad practical relevance.

New model species for arctic-alpine plant molecular ecology.

Arctic and alpine, high latitude and high elevation environments are one of the most stressful environments for species to inhabit. This harshness manifests itself in lower species richness in comparison to more southern vegetation zones (Francis & Currie, 2003). Furthermore, the climatic oscillations-past and predicted-have the most dramatic effect on these ecosystems. For example, in regions of continental ice sheets-the northernmost part of Western Europe and North America-the Arctic species assemblages are no older than a few thousands of years, which is a relatively short period from an evolutionary perspective. Although similar environments may have existed further south during the Ice Age, allowing some preadaptation for the Arctic species, the current habitat is a unique combination of environmental factors such as the climate, soil, bedrock, and photoperiod. Hence, understanding the evolutionary forces shaping Arctic-alpine species will be important for predicting these vulnerable environments' population viability and adaptive potential in the future. In this issue of Molecular Ecology Resources, Nowak et al. (Molecular Ecology Resources) present extensive genome-wide resources for an Arctic-alpine plant Draba nivalis. This adds a valuable new member into the cabbage family models for evolutionary genetics and adaptation studies, to accompany e.g., Arabidopsis (Nature Genetics, 43, 476; Nature, 408, 796), Arabis (Nature Plants, 1, 14023) and Capsella (Nature Genetics, 45, 831). A whole new avenue will open up for molecular ecological studies not only for D. nivalis, but the whole large Draba genus with its diverse ecological and evolutionary characteristics.

Selection patterns on early-life phenotypic traits in Pinus sylvestris are associated with precipitation and temperature along a climatic gradient in Europe.

Understanding the dynamics of selection is key to predicting the response of tree species to new environmental conditions in the current context of climate change. However, selection patterns acting on early recruitment stages and their climatic drivers remain largely unknown in most tree species, despite being a critical period of their life cycle. We measured phenotypic selection on Pinus sylvestris seed mass, emergence time and early growth rate over 2 yr in four common garden experiments established along the latitudinal gradient of the species in Europe. Significant phenotypic plasticity and among-population genetic variation were found for all measured phenotypic traits. Heat and drought negatively affected fitness in the southern sites, but heavy rainfalls also decreased early survival in middle latitudes. Climate-driven directional selection was found for higher seed mass and earlier emergence time, while the form of selection on seedling growth rates differed among sites and populations. Evidence of adaptive and maladaptive phenotypic plasticity was found for emergence time and early growth rate, respectively. Seed mass, emergence time and early growth rate have an adaptive role in the early stages of P. sylvestris and climate strongly influences the patterns of selection on these fitness-related traits.

Long-Term Reciprocal Gene Flow in Wild and Domestic Geese Reveals Complex Domestication History.

Hybridization has frequently been observed between wild and domestic species and can substantially impact genetic diversity of both counterparts. Geese show some of the highest levels of interspecific hybridization across all bird orders, and two of the goose species in the genus Anser have been domesticated providing an excellent opportunity for a joint study of domestication and hybridization. Until now, knowledge of the details of the goose domestication process has come from archaeological findings and historical writings supplemented with a few studies based on mitochondrial DNA. Here, we used genome-wide markers to make the first genome-based inference of the timing of European goose domestication. We also analyzed the impact of hybridization on the genome-wide genetic variation in current populations of the European domestic goose and its wild progenitor: the graylag goose (Anser anser). Our dataset consisted of 58 wild graylags sampled around Eurasia and 75 domestic geese representing 14 breeds genotyped for 33,527 single nucleotide polymorphisms. Demographic reconstruction and clustering analysis suggested that divergence between wild and domestic geese around 5,300 generations ago was followed by long-term genetic exchange, and that graylag populations have 3.2-58.0% admixture proportions with domestic geese, with distinct geographic patterns. Surprisingly, many modern European breeds share considerable (> 10%) ancestry with the Chinese domestic geese that is derived from the swan goose Anser cygnoid We show that the domestication process can progress despite continued and pervasive gene flow from the wild form.

Genomics of Clinal Local Adaptation in Pinus sylvestris Under Continuous Environmental and Spatial Genetic Setting.

Understanding the consequences of local adaptation at the genomic diversity is a central goal in evolutionary genetics of natural populations. In species with large continuous geographical distributions the phenotypic signal of local adaptation is frequently clear, but the genetic basis often remains elusive. We examined the patterns of genetic diversity in Pinus sylvestris, a keystone species in many Eurasian ecosystems with a huge distribution range and decades of forestry research showing that it is locally adapted to the vast range of environmental conditions. Making P. sylvestris an even more attractive subject of local adaptation study, population structure has been shown to be weak previously and in this study. However, little is known about the molecular genetic basis of adaptation, as the massive size of gymnosperm genomes has prevented large scale genomic surveys. We generated a both geographically and genomically extensive dataset using a targeted sequencing approach. By applying divergence-based and landscape genomics methods we identified several loci contributing to local adaptation, but only few with large allele frequency changes across latitude. We also discovered a very large (ca. 300 Mbp) putative inversion potentially under selection, which to our knowledge is the first such discovery in conifers. Our results call for more detailed analysis of structural variation in relation to genomic basis of local adaptation, emphasize the lack of large effect loci contributing to local adaptation in the coding regions and thus point out the need for more attention toward multi-locus analysis of polygenic adaptation.

275 years of forestry meets genomics in Pinus sylvestris.

Pinus sylvestris has a long history of basic and applied research that is relevant for both forestry and evolutionary studies. Its patterns of adaptive variation and role in forest economic and ecological systems have been studied extensively for nearly 275 years, detailed demography for a 100 years and mating system more than 50 years. However, its reference genome sequence is not yet available and genomic studies have been lagging compared to, for example, Pinus taeda and Picea abies, two other economically important conifers. Despite the lack of reference genome, many modern genomic methods are applicable for a more detailed look at its biological characteristics. For example, RNA-seq has revealed a complex transcriptional landscape and targeted DNA sequencing displays an excess of rare variants and geographically homogenously distributed molecular genetic diversity. Current DNA and RNA resources can be used as a reference for gene expression studies, SNP discovery, and further targeted sequencing. In the future, specific consequences of the large genome size, such as functional effects of regulatory open chromatin regions and transposable elements, should be investigated more carefully. For forest breeding and long-term management purposes, genomic data can help in assessing the genetic basis of inbreeding depression and the application of genomic tools for genomic prediction and relatedness estimates. Given the challenges of breeding (long generation time, no easy vegetative propagation) and the economic importance, application of genomic tools has a potential to have a considerable impact. Here, we explore how genomic characteristics of P. sylvestris, such as rare alleles and the low extent of linkage disequilibrium, impact the applicability and power of the tools.

Utilization of Tissue Ploidy Level Variation in de Novo Transcriptome Assembly of Pinus sylvestris.

Compared to angiosperms, gymnosperms lag behind in the availability of assembled and annotated genomes. Most genomic analyses in gymnosperms, especially conifer tree species, rely on the use of de novo assembled transcriptomes. However, the level of allelic redundancy and transcript fragmentation in these assembled transcriptomes, and their effect on downstream applications have not been fully investigated. Here, we assessed three assembly strategies for short-reads data, including the utility of haploid megagametophyte tissue during de novo assembly as single-allele guides, for six individuals and five different tissues in Pinus sylvestris We then contrasted haploid and diploid tissue genotype calls obtained from the assembled transcriptomes to evaluate the extent of paralog mapping. The use of the haploid tissue during assembly increased its completeness without reducing the number of assembled transcripts. Our results suggest that current strategies that rely on available genomic resources as guidance to minimize allelic redundancy are less effective than the application of strategies that cluster redundant assembled transcripts. The strategy yielding the lowest levels of allelic redundancy among the assembled transcriptomes assessed here was the generation of SuperTranscripts with Lace followed by CD-HIT clustering. However, we still observed some levels of heterozygosity (multiple gene fragments per transcript reflecting allelic redundancy) in this assembled transcriptome on the haploid tissue, indicating that further filtering is required before using these assemblies for downstream applications. We discuss the influence of allelic redundancy when these reference transcriptomes are used to select regions for probe design of exome capture baits and for estimation of population genetic diversity.

Genome-Wide Analysis of Colonization History and Concomitant Selection in Arabidopsis lyrata.

The high climatic variability in the past hundred thousand years has affected the demographic and adaptive processes in many species, especially in boreal and temperate regions undergoing glacial cycles. This has also influenced the patterns of genome-wide nucleotide variation, but the details of these effects are largely unknown. Here we study the patterns of genome-wide variation to infer colonization history and patterns of selection of the perennial herb species Arabidopsis lyrata, in locally adapted populations from different parts of its distribution range (Germany, UK, Norway, Sweden, and USA) representing different environmental conditions. Using site frequency spectra based demographic modeling, we found strong reduction in the effective population size of the species in general within the past 100,000 years, with more pronounced effects in the colonizing populations. We further found that the northwestern European A. lyrata populations (UK and Scandinavian) are more closely related to each other than with the Central European populations, and coalescent based population split modeling suggests that western European and Scandinavian populations became isolated relatively recently after the glacial retreat. We also highlighted loci showing evidence for local selection associated with the Scandinavian colonization. The results presented here give new insights into postglacial Scandinavian colonization history and its genome-wide effects.

No evidence of prenatal diversifying selection at locus or supertype levels in the dog MHC class II loci.

BACKGROUND: Despite decades of studying, the mechanisms maintaining high diversity in the genes of the Major Histocompatibility Complex (MHC) are still puzzling scientists. In addition to pathogen recognition and other functions, MHC molecules may act prenatally in mate choice and in maternal-foetal interactions. These interactions are potential selective mechanisms that increase genetic diversity in the MHC. During pregnancy, immune response has a dual role: the foetus represents foreign tissue compared to mother, but histo-incompatibility is required for successful pregnancy. We have studied the prenatal selection in MHC class II loci (DLA-DQA1, DLA-DQB1 and DLA-DRB1) in domestic dogs by comparing the observed and expected offspring genotype proportions in 110 dog families. Several potential selection targets were addressed, including the peptide-binding site, the MHC locus, three-locus haplotype and supertype levels. For the supertype analysis, the first canine supertype classification was created based on in silico analysis of peptide-binding amino-acid polymorphism. RESULTS: In most loci and levels, no deviation from the expected genotype frequencies was observed. However, one peptide-binding site in DLA-DRB1 had an excess of heterozygotes among the offspring. In addition, if the father shared a DLA-DRB1 allele with the mother, that allele was inherited by the offspring more frequently than expected, suggesting the selective advantage of a histo-compatible foetus, in contrast to our expectations. CONCLUSIONS: We conclude that there is some evidence of post-copulatory selection at nucleotide site level in the MHC loci of pet dogs. But due to no indication of selection at locus, three-locus, or supertype levels, we estimated that the prenatal selection coefficient is less than 0.3 in domestic dogs and very likely other factors are more important in maintaining the genetic diversity in MHC loci.

Natural variation in teosinte at the domestication locus teosinte branched1 (tb1).

The teosinte branched1(tb1) gene is a major QTL controlling branching differences between maize and its wild progenitor, teosinte. The insertion of a transposable element (Hopscotch) upstream of tb1 is known to enhance the gene's expression, causing reduced tillering in maize. Observations of the maize tb1 allele in teosinte and estimates of an insertion age of the Hopscotch that predates domestication led us to investigate its prevalence and potential role in teosinte. We assessed the prevalence of the Hopscotch element across an Americas-wide sample of 837 maize and teosinte individuals using a co-dominant PCR assay. Additionally, we calculated population genetic summaries using sequence data from a subset of individuals from four teosinte populations and collected phenotypic data using seed from a single teosinte population where Hopscotch was found segregating at high frequency. Genotyping results indicate the Hopscotch element is found in a number of teosinte populations and linkage disequilibrium near tb1 does not support recent introgression from maize. Population genetic signatures are consistent with selection on the tb1 locus, revealing a potential ecological role, but a greenhouse experiment does not detect a strong association between the Hopscotch and tillering in teosinte. Our findings suggest the role of Hopscotch differs between maize and teosinte. Future work should assess tb1 expression levels in teosinte with and without the Hopscotch and more comprehensively phenotype teosinte to assess the ecological significance of the Hopscotch insertion and, more broadly, the tb1 locus in teosinte.