@article{vallebueno-estrada_unified_2026,
	title = {Unified {Multi}-{Caller} {Ensemble} ({UME}) {Generates} an {Unbiased} {Maize} {Haplotype} {Map} for {Variable} {Coverage} {Whole} {Genome} {Data}},
	volume = {26},
	copyright = {© 2026 The Author(s). Molecular Ecology Resources published by John Wiley \& Sons Ltd.},
	issn = {1755-0998},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/1755-0998.70150},
	doi = {10.1111/1755-0998.70150},
	abstract = {We present a novel diversity-focused haplotype map (HapMap) that characterizes over 64.5 million maize (Zea mays ssp. mays) single nucleotide polymorphisms (SNPs) genotyped across 818 individuals from diverse backgrounds. This HapMap aims to balance the variation obtained from domesticated landraces and inbred lines, outgroup Zea spp. and more distant Tripsacum spp. in order to minimize ascertainment bias for diversity studies. Included individuals derive from public data from various experimental setups and coverages, which is challenging for standard SNP callers to accommodate. We provide evidence of coverage biases associated with standard callers that influence resulting variation and introduce a novel approach called Unified Multi-Caller Ensemble (UME), which enhances variant calling accuracy in low-coverage and mixed-coverage genomic datasets. UME corrects for coverage bias resulting from inter-sample coverage heterogeneity by leveraging evidence from variant callers with orthogonal strategies, re-calibrating the error probabilities across callers to minimize the impact of error biases inherent to a given caller. It outperforms individual strategies and excels in de novo variant calling, taking advantage of instances of higher depth reads, even in low coverage individuals, while preserving biologically informative variant relationships across coverage levels. An important feature of UME is the independence from population allele frequencies in the discovery panel, thus avoiding ascertainment bias resulting from unbalanced input genetic diversity. Discovered variants are less affected by ascertainment bias because no population filtering is used, and the full diversity of SNPs is retained in the final variant call set to maximize the utility of the dataset for production calling newly sequenced samples. We present a strategy for filtering the recalibrated error profiles that relies on maximizing demographic signals to retain genetic relationships within the population while reducing sequencing error. After the variant discovery phase, we employ the UME production stage, which enriches genotype calling across all coverage levels, benefiting low-coverage samples. Error introduced in this process is removed through subsequent filtering. Using this approach, we generated a coverage bias-controlled maize HapMap database, providing a comprehensive representation of maize accessions and emphasizing landrace diversity. This diverse panel of domesticated maize and outgroups from across the Americas enables accurate genotyping in low-coverage samples while offering crucial context for interpreting diversity, particularly for natural diversity and paleogenomic analyses.},
	language = {en},
	number = {5},
	urldate = {2026-07-31},
	journal = {Molecular Ecology Resources},
	author = {Vallebueno-Estrada, Miguel and Swarts, Kelly},
	year = {2026},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/1755-0998.70150},
	keywords = {HapMap, coverage bias, ensemble approaches, maize, variant calling},
	pages = {e70150},
}

We present a novel diversity-focused haplotype map (HapMap) that characterizes over 64.5 million maize (Zea mays ssp. mays) single nucleotide polymorphisms (SNPs) genotyped across 818 individuals from diverse backgrounds. This HapMap aims to balance the variation obtained from domesticated landraces and inbred lines, outgroup Zea spp. and more distant Tripsacum spp. in order to minimize ascertainment bias for diversity studies. Included individuals derive from public data from various experimental setups and coverages, which is challenging for standard SNP callers to accommodate. We provide evidence of coverage biases associated with standard callers that influence resulting variation and introduce a novel approach called Unified Multi-Caller Ensemble (UME), which enhances variant calling accuracy in low-coverage and mixed-coverage genomic datasets. UME corrects for coverage bias resulting from inter-sample coverage heterogeneity by leveraging evidence from variant callers with orthogonal strategies, re-calibrating the error probabilities across callers to minimize the impact of error biases inherent to a given caller. It outperforms individual strategies and excels in de novo variant calling, taking advantage of instances of higher depth reads, even in low coverage individuals, while preserving biologically informative variant relationships across coverage levels. An important feature of UME is the independence from population allele frequencies in the discovery panel, thus avoiding ascertainment bias resulting from unbalanced input genetic diversity. Discovered variants are less affected by ascertainment bias because no population filtering is used, and the full diversity of SNPs is retained in the final variant call set to maximize the utility of the dataset for production calling newly sequenced samples. We present a strategy for filtering the recalibrated error profiles that relies on maximizing demographic signals to retain genetic relationships within the population while reducing sequencing error. After the variant discovery phase, we employ the UME production stage, which enriches genotype calling across all coverage levels, benefiting low-coverage samples. Error introduced in this process is removed through subsequent filtering. Using this approach, we generated a coverage bias-controlled maize HapMap database, providing a comprehensive representation of maize accessions and emphasizing landrace diversity. This diverse panel of domesticated maize and outgroups from across the Americas enables accurate genotyping in low-coverage samples while offering crucial context for interpreting diversity, particularly for natural diversity and paleogenomic analyses.

@article{wu_population_2025,
	title = {Population genomics of \textit{{Marchantia} polymorpha} subsp. \textit{ruderalis} reveals evidence of climate adaptation},
	volume = {35},
	issn = {0960-9822},
	url = {https://www.sciencedirect.com/science/article/pii/S0960982225000089},
	doi = {10.1016/j.cub.2025.01.008},
	abstract = {Sexual reproduction results in the development of haploid and diploid cell states during the life cycle. In bryophytes, the dominant multicellular haploid phase produces motile sperm that swim through water to the egg to effect fertilization from which a relatively small diploid phase develops. In angiosperms, the reduced multicellular haploid phase produces non-motile sperm that is delivered to the egg through a pollen tube to effect fertilization from which the dominant diploid phase develops. These different life cycle characteristics are likely to impact the distribution of genetic variation among populations. However, little is known about the distribution of genetic variation among wild populations of bryophytes. To investigate how genetic variation is distributed among populations of a bryophyte and to establish the foundation for population genetics research in bryophytes, we described the genetic diversity of collections of Marchantia polymorpha subsp. ruderalis, a cosmopolitan ruderal liverwort. We identified 78 genetically unique (non-clonal) from a total of 209 sequenced accessions collected from 37 sites in Europe and Japan. There was no detectable population structure among European populations but significant genetic differentiation between Japanese and European populations. By associating genetic variation across the genome with global climate data, we showed that temperature and precipitation influence the frequency of potentially adaptive alleles. This collection establishes the core of an experimental platform that exploits natural genetic variation to answer diverse questions in biology.},
	number = {5},
	urldate = {2025-03-28},
	journal = {Current Biology},
	author = {Wu, Shuangyang and Jandrasits, Katharina and Swarts, Kelly and Roetzer, Johannes and Akimcheva, Svetlana and Shimamura, Masaki and Hisanaga, Tetsuya and Berger, Frédéric and Dolan, Liam},
	month = mar,
	year = {2025},
	pages = {970--980.e3},
}

Sexual reproduction results in the development of haploid and diploid cell states during the life cycle. In bryophytes, the dominant multicellular haploid phase produces motile sperm that swim through water to the egg to effect fertilization from which a relatively small diploid phase develops. In angiosperms, the reduced multicellular haploid phase produces non-motile sperm that is delivered to the egg through a pollen tube to effect fertilization from which the dominant diploid phase develops. These different life cycle characteristics are likely to impact the distribution of genetic variation among populations. However, little is known about the distribution of genetic variation among wild populations of bryophytes. To investigate how genetic variation is distributed among populations of a bryophyte and to establish the foundation for population genetics research in bryophytes, we described the genetic diversity of collections of Marchantia polymorpha subsp. ruderalis, a cosmopolitan ruderal liverwort. We identified 78 genetically unique (non-clonal) from a total of 209 sequenced accessions collected from 37 sites in Europe and Japan. There was no detectable population structure among European populations but significant genetic differentiation between Japanese and European populations. By associating genetic variation across the genome with global climate data, we showed that temperature and precipitation influence the frequency of potentially adaptive alleles. This collection establishes the core of an experimental platform that exploits natural genetic variation to answer diverse questions in biology.

@article{polacek_automation_2023,
	title = {Automation of tree-ring detection and measurements using deep learning},
	volume = {14},
	copyright = {© 2023 GMI - Gregor Mendel Institute of Molecular Plant Biology. Methods in Ecology and Evolution published by John Wiley \& Sons Ltd on behalf of British Ecological Society.},
	issn = {2041-210X},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/2041-210X.14183},
	doi = {10.1111/2041-210X.14183},
	abstract = {Core samples from trees are a critical reservoir of ecological information, informing our understanding of past climates, as well as contemporary ecosystem responses to global change. Manual measurements of annual growth rings in trees are slow, labour-intensive and subject to human bias, hindering the generation of big datasets. We present an alternative, neural network-based implementation that automates detection and measurement of tree-ring boundaries from coniferous species. We trained our Mask R-CNN extensively on over 8000 manually annotated ring boundaries from microscope-imaged Norway Spruce Picea abies increment cores. We assessed the performance of the trained model after post-processing on real-world data generated from our core processing pipeline. The CNN after post-processing performed well, with recognition of over 98\% of ring boundaries (recall) with a precision in detection of 96\% when tested on real-world data. Additionally, we have implemented automatic measurements based on minimum distance between rings. With minimal editing for missed ring detections, these measurements were 98\% correlated with human measurements of the same samples. Tests on other three conifer species demonstrate that the CNN generalizes well to other species with similar structure. We demonstrate the efficacy of automating the measurement of growth increment in tree core samples. Our CNN-based system provides high predictive performance in terms of both tree-ring detection and growth rate determination. Our application is readily deployable as a Docker container and requires only basic command line skills. Additionally, an easy re-training option allows users to expand capabilities to other wood types. Application outputs include both editable annotations of predictions as well as ring-width measurements in a commonly used .pos format, facilitating the efficient generation of large ring-width measurement datasets from increment core samples, an important source of environmental data.},
	language = {en},
	number = {9},
	urldate = {2024-03-22},
	journal = {Methods in Ecology and Evolution},
	author = {Poláček, Miroslav and Arizpe, Alexis and Hüther, Patrick and Weidlich, Lisa and Steindl, Sonja and Swarts, Kelly},
	year = {2023},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1111/2041-210X.14183},
	keywords = {automation, computer vision, mask R-CNN, phenotyping, tree rings},
	pages = {2233--2242},
}

Core samples from trees are a critical reservoir of ecological information, informing our understanding of past climates, as well as contemporary ecosystem responses to global change. Manual measurements of annual growth rings in trees are slow, labour-intensive and subject to human bias, hindering the generation of big datasets. We present an alternative, neural network-based implementation that automates detection and measurement of tree-ring boundaries from coniferous species. We trained our Mask R-CNN extensively on over 8000 manually annotated ring boundaries from microscope-imaged Norway Spruce Picea abies increment cores. We assessed the performance of the trained model after post-processing on real-world data generated from our core processing pipeline. The CNN after post-processing performed well, with recognition of over 98% of ring boundaries (recall) with a precision in detection of 96% when tested on real-world data. Additionally, we have implemented automatic measurements based on minimum distance between rings. With minimal editing for missed ring detections, these measurements were 98% correlated with human measurements of the same samples. Tests on other three conifer species demonstrate that the CNN generalizes well to other species with similar structure. We demonstrate the efficacy of automating the measurement of growth increment in tree core samples. Our CNN-based system provides high predictive performance in terms of both tree-ring detection and growth rate determination. Our application is readily deployable as a Docker container and requires only basic command line skills. Additionally, an easy re-training option allows users to expand capabilities to other wood types. Application outputs include both editable annotations of predictions as well as ring-width measurements in a commonly used .pos format, facilitating the efficient generation of large ring-width measurement datasets from increment core samples, an important source of environmental data.

@article{vallebueno-estrada_domestication_2023,
	title = {Domestication and lowland adaptation of coastal preceramic maize from {Paredones}, {Peru}},
	volume = {12},
	issn = {2050-084X},
	url = {https://doi.org/10.7554/eLife.83149},
	doi = {10.7554/eLife.83149},
	abstract = {Archaeological cobs from Paredones and Huaca Prieta (Peru) represent some of the oldest maize known to date, yet they present relevant phenotypic traits corresponding to domesticated maize. This contrasts with the earliest Mexican macro-specimens from Guila Naquitz and San Marcos, which are phenotypically intermediate for these traits, even though they date more recently in time. To gain insights into the origins of ancient Peruvian maize, we sequenced DNA from three Paredones specimens dating {\textasciitilde}6700–5000 calibrated years before present (BP), conducting comparative analyses with two teosinte subspecies (Zea mays ssp. mexicana and parviglumis) and extant maize, that include highland and lowland landraces from Mesoamerica and South America. We show that Paredones maize originated from the same domestication event as Mexican maize and was domesticated by {\textasciitilde}6700 BP, implying rapid dispersal followed by improvement. Paredones maize shows no relevant gene flow from mexicana, smaller than that observed in teosinte parviglumis. Thus, Paredones samples represent the only maize without confounding mexicana variation found to date. It also harbors significantly fewer alleles previously found to be adaptive to highlands, but not of alleles adaptive to lowlands, supporting a lowland migration route. Our overall results imply that Paredones maize originated in Mesoamerica, arrived in Peru without mexicana introgression through a rapid lowland migration route, and underwent improvements in both Mesoamerica and South America.},
	urldate = {2024-03-22},
	journal = {eLife},
	publisher = {eLife Sciences Publications, Ltd},
	author = {Vallebueno-Estrada, Miguel and Hernández-Robles, Guillermo G and González-Orozco, Eduardo and Lopez-Valdivia, Ivan and Rosales Tham, Teresa and Vásquez Sánchez, Víctor and Swarts, Kelly and Dillehay, Tom D and Vielle-Calzada, Jean-Philippe and Montiel, Rafael},
	editor = {Weigel, Detlef},
	month = apr,
	year = {2023},
	keywords = {domestication, lowlands, paleogenomics, paredones},
	pages = {e83149},
}

Archaeological cobs from Paredones and Huaca Prieta (Peru) represent some of the oldest maize known to date, yet they present relevant phenotypic traits corresponding to domesticated maize. This contrasts with the earliest Mexican macro-specimens from Guila Naquitz and San Marcos, which are phenotypically intermediate for these traits, even though they date more recently in time. To gain insights into the origins of ancient Peruvian maize, we sequenced DNA from three Paredones specimens dating ~6700–5000 calibrated years before present (BP), conducting comparative analyses with two teosinte subspecies (Zea mays ssp. mexicana and parviglumis) and extant maize, that include highland and lowland landraces from Mesoamerica and South America. We show that Paredones maize originated from the same domestication event as Mexican maize and was domesticated by ~6700 BP, implying rapid dispersal followed by improvement. Paredones maize shows no relevant gene flow from mexicana, smaller than that observed in teosinte parviglumis. Thus, Paredones samples represent the only maize without confounding mexicana variation found to date. It also harbors significantly fewer alleles previously found to be adaptive to highlands, but not of alleles adaptive to lowlands, supporting a lowland migration route. Our overall results imply that Paredones maize originated in Mesoamerica, arrived in Peru without mexicana introgression through a rapid lowland migration route, and underwent improvements in both Mesoamerica and South America.

@article{morales_heritable_2022,
	title = {Heritable and {Climatic} {Sources} of {Variation} in {Juvenile} {Tree} {Growth} in an {Austrian} {Common} {Garden} {Experiment} of {Central} {European} {Norway} {Spruce} {Populations}},
	volume = {13},
	copyright = {http://creativecommons.org/licenses/by/3.0/},
	issn = {1999-4907},
	url = {https://www.mdpi.com/1999-4907/13/5/809},
	doi = {10.3390/f13050809},
	abstract = {We leveraged publicly available data on juvenile tree height of 299 Central European Norway spruce populations grown in a common garden experiment across 24 diverse trial locations in Austria and weather data from the trial locations and population provenances to parse the heritable and climatic components of juvenile tree height variation. Principal component analysis of geospatial and weather variables demonstrated high interannual variation among trial environments, largely driven by differences in precipitation, and separation of population provenances based on altitude, temperature, and snowfall. Tree height was highly heritable and modeling the covariance between populations and trial environments based on climatic data led to more stable estimation of heritability and population × environment variance. Climatic similarity among population provenances was highly predictive of population × environment estimates for tree height.},
	language = {en},
	number = {5},
	urldate = {2024-03-22},
	journal = {Forests},
	publisher = {Multidisciplinary Digital Publishing Institute},
	author = {Morales, Laura and Swarts, Kelly},
	month = may,
	year = {2022},
	note = {Number: 5},
	keywords = {Norway spruce, climate, genotype-by-environment, prediction, tree height},
	pages = {809},
}

We leveraged publicly available data on juvenile tree height of 299 Central European Norway spruce populations grown in a common garden experiment across 24 diverse trial locations in Austria and weather data from the trial locations and population provenances to parse the heritable and climatic components of juvenile tree height variation. Principal component analysis of geospatial and weather variables demonstrated high interannual variation among trial environments, largely driven by differences in precipitation, and separation of population provenances based on altitude, temperature, and snowfall. Tree height was highly heritable and modeling the covariance between populations and trial environments based on climatic data led to more stable estimation of heritability and population × environment variance. Climatic similarity among population provenances was highly predictive of population × environment estimates for tree height.

@article{korolyova_last_2022,
	title = {The {Last} {Trees} {Standing}: {Climate} modulates tree survival factors during a prolonged bark beetle outbreak in {Europe}},
	volume = {322},
	issn = {0168-1923},
	shorttitle = {The {Last} {Trees} {Standing}},
	url = {https://www.sciencedirect.com/science/article/pii/S0168192322002143},
	doi = {10.1016/j.agrformet.2022.109025},
	abstract = {Plant traits are an expression of strategic tradeoffs in plant performance that determine variation in allocation of finite resources to alternate physiological functions. Climate factors interact with plant traits to mediate tree survival. This study investigated survival dynamics in Norway spruce (Picea abies) in relation to tree-level morphological traits during a prolonged multi-year outbreak of the bark beetle, Ips typographus, in Central Europe. We acquired datasets describing the trait attributes of individual spruce using remote sensing and field surveys. We used nonlinear regression in a hypothesis-driven framework to quantify survival probability as a function of tree size, crown morphology, intraspecific competition and a growing season water balance. Extant spruce trees that persisted through the outbreak were spatially clustered, suggesting that survival was a non-random process. Larger diameter trees were more susceptible to bark beetles, reflecting either life history tradeoffs or a dynamic interaction between defense capacity and insect aggregation behavior. Competition had a strong negative effect on survival, presumably through resource limitation. Trees with more extensive crowns were buffered against bark beetles, ostensibly by a more robust photosynthetic capability and greater carbon reserves. The outbreak spanned a warming trend and conditions of anomalous aridity. Sustained water limitation during this period amplified the consequences of other factors, rendering even smaller trees vulnerable to colonization by insects. Our results are in agreement with prior research indicating that climate change has the potential to intensify bark beetle activity. However, forest outcomes will depend on complex cross-scale interactions between global climate trends and tree-level trait factors, as well as feedback effects associated with landscape patterns of stand structural diversity.},
	urldate = {2024-03-22},
	journal = {Agricultural and Forest Meteorology},
	author = {Korolyova, Nataliya and Buechling, Arne and Ďuračiová, Renata and Zabihi, Khodabakhsh and Turčáni, Marek and Svoboda, Miroslav and Bláha, Jaromír and Swarts, Kelly and Poláček, Miroslav and Hradecký, Jaromir and Červenka, Jaroslav and Němčák, Pavel and Schlyter, Fredrik and Jakuš, Rastislav},
	month = jul,
	year = {2022},
	keywords = {Carbon, Climate change, Competition, Crown shading, Drought, Tree survival},
	pages = {109025},
}

Plant traits are an expression of strategic tradeoffs in plant performance that determine variation in allocation of finite resources to alternate physiological functions. Climate factors interact with plant traits to mediate tree survival. This study investigated survival dynamics in Norway spruce (Picea abies) in relation to tree-level morphological traits during a prolonged multi-year outbreak of the bark beetle, Ips typographus, in Central Europe. We acquired datasets describing the trait attributes of individual spruce using remote sensing and field surveys. We used nonlinear regression in a hypothesis-driven framework to quantify survival probability as a function of tree size, crown morphology, intraspecific competition and a growing season water balance. Extant spruce trees that persisted through the outbreak were spatially clustered, suggesting that survival was a non-random process. Larger diameter trees were more susceptible to bark beetles, reflecting either life history tradeoffs or a dynamic interaction between defense capacity and insect aggregation behavior. Competition had a strong negative effect on survival, presumably through resource limitation. Trees with more extensive crowns were buffered against bark beetles, ostensibly by a more robust photosynthetic capability and greater carbon reserves. The outbreak spanned a warming trend and conditions of anomalous aridity. Sustained water limitation during this period amplified the consequences of other factors, rendering even smaller trees vulnerable to colonization by insects. Our results are in agreement with prior research indicating that climate change has the potential to intensify bark beetle activity. However, forest outcomes will depend on complex cross-scale interactions between global climate trends and tree-level trait factors, as well as feedback effects associated with landscape patterns of stand structural diversity.

@article{yost_situ_2021,
	title = {An \textit{in situ} and morphometric study of maize (\textit{{Zea} mays} {L}.) cob rondel phytoliths from {Southwestern} {North} {American} landraces},
	volume = {35},
	issn = {2352-409X},
	url = {https://www.sciencedirect.com/science/article/pii/S2352409X2030523X},
	doi = {10.1016/j.jasrep.2020.102732},
	abstract = {We present the first comprehensive computer-assisted morphometric analysis of microscopic rondel11As per the International Code for Phytolith Nomenclature 2.0 the names of recognized phytolith morphotypes are written in small caps in this report (Neumann et al., 2019). phytoliths (plant opal microfossils) produced in the cobs of 24 historic Southwestern North American landraces of maize (Zea mays L.) after all were grown in a well-documented agronomic field study. We also present an in situ study of the location of rondel phytolith production within the maize cob and provide a detailed review of previous maize phytolith studies. We found that glumes contained abundant rondel phytoliths throughout the tissue; however, lemma/palea tissue contained no phytoliths. In contrast, cupule tissue had some areas with abundant phytoliths, some with fewer scattered phytoliths, and vast areas that contained no rondel phytoliths. The rondel-rich areas appear to be where the glumes had once attached to the cupule and may be remnants of glume tissue adhering to the cupule. From the morphometric study, we found there were significant differences in the size morphometries of glume rondels depending on their cob location (top, middle, base) but no significant differences in shape morphometries. Using shape morphometries, we could not discriminate reliably among maize cob rondel phytoliths produced by the diverse landraces considered. The inclusion of morphometrics from areas in addition to or in combination with the outer periclinal surface may allow for some discrimination of maize landraces and is an avenue that should be explored further. Although our approach was not successful at identifying differences between essentially modern landraces, there may be significant rondel phytolith morphometric differences between wild, progenitor, and domesticated Zea.},
	urldate = {2024-03-22},
	journal = {Journal of Archaeological Science: Reports},
	author = {Yost, Chad L. and Michas, McCaela and Adams, Karen R. and Swarts, Kelly and Puseman, Kathryn and Ball, Terry},
	month = feb,
	year = {2021},
	keywords = {Glumes, Landrace, Maize, Morphometrics, Phytoliths},
	pages = {102732},
}

We present the first comprehensive computer-assisted morphometric analysis of microscopic rondel11As per the International Code for Phytolith Nomenclature 2.0 the names of recognized phytolith morphotypes are written in small caps in this report (Neumann et al., 2019). phytoliths (plant opal microfossils) produced in the cobs of 24 historic Southwestern North American landraces of maize (Zea mays L.) after all were grown in a well-documented agronomic field study. We also present an in situ study of the location of rondel phytolith production within the maize cob and provide a detailed review of previous maize phytolith studies. We found that glumes contained abundant rondel phytoliths throughout the tissue; however, lemma/palea tissue contained no phytoliths. In contrast, cupule tissue had some areas with abundant phytoliths, some with fewer scattered phytoliths, and vast areas that contained no rondel phytoliths. The rondel-rich areas appear to be where the glumes had once attached to the cupule and may be remnants of glume tissue adhering to the cupule. From the morphometric study, we found there were significant differences in the size morphometries of glume rondels depending on their cob location (top, middle, base) but no significant differences in shape morphometries. Using shape morphometries, we could not discriminate reliably among maize cob rondel phytoliths produced by the diverse landraces considered. The inclusion of morphometrics from areas in addition to or in combination with the outer periclinal surface may allow for some discrimination of maize landraces and is an avenue that should be explored further. Although our approach was not successful at identifying differences between essentially modern landraces, there may be significant rondel phytolith morphometric differences between wild, progenitor, and domesticated Zea.

@article{hu_genome_2021,
	title = {Genome assembly and population genomic analysis provide insights into the evolution of modern sweet corn},
	volume = {12},
	copyright = {2021 The Author(s)},
	issn = {2041-1723},
	url = {https://www.nature.com/articles/s41467-021-21380-4},
	doi = {10.1038/s41467-021-21380-4},
	abstract = {Sweet corn is one of the most important vegetables in the United States and Canada. Here, we present a de novo assembly of a sweet corn inbred line Ia453 with the mutated shrunken2-reference allele (Ia453-sh2). This mutation accumulates more sugar and is present in most commercial hybrids developed for the processing and fresh markets. The ten pseudochromosomes cover 92\% of the total assembly and 99\% of the estimated genome size, with a scaffold N50 of 222.2 Mb. This reference genome completely assembles the large structural variation that created the mutant sh2-R allele. Furthermore, comparative genomics analysis with six field corn genomes highlights differences in single-nucleotide polymorphisms, structural variations, and transposon composition. Phylogenetic analysis of 5,381 diverse maize and teosinte accessions reveals genetic relationships between sweet corn and other types of maize. Our results show evidence for a common origin in northern Mexico for modern sweet corn in the U.S. Finally, population genomic analysis identifies regions of the genome under selection and candidate genes associated with sweet corn traits, such as early flowering, endosperm composition, plant and tassel architecture, and kernel row number. Our study provides a high-quality reference-genome sequence to facilitate comparative genomics, functional studies, and genomic-assisted breeding for sweet corn.},
	language = {en},
	number = {1},
	urldate = {2024-03-22},
	journal = {Nature Communications},
	publisher = {Nature Publishing Group},
	author = {Hu, Ying and Colantonio, Vincent and Müller, Bárbara S. F. and Leach, Kristen A. and Nanni, Adalena and Finegan, Christina and Wang, Bo and Baseggio, Matheus and Newton, Carter J. and Juhl, Emily M. and Hislop, Lillian and Gonzalez, Juan M. and Rios, Esteban F. and Hannah, L. Curtis and Swarts, Kelly and Gore, Michael A. and Hennen-Bierwagen, Tracie A. and Myers, Alan M. and Settles, A. Mark and Tracy, William F. and Resende, Marcio F. R.},
	month = feb,
	year = {2021},
	keywords = {Agricultural genetics, Evolutionary biology, Plant breeding},
	pages = {1227},
}

Sweet corn is one of the most important vegetables in the United States and Canada. Here, we present a de novo assembly of a sweet corn inbred line Ia453 with the mutated shrunken2-reference allele (Ia453-sh2). This mutation accumulates more sugar and is present in most commercial hybrids developed for the processing and fresh markets. The ten pseudochromosomes cover 92% of the total assembly and 99% of the estimated genome size, with a scaffold N50 of 222.2 Mb. This reference genome completely assembles the large structural variation that created the mutant sh2-R allele. Furthermore, comparative genomics analysis with six field corn genomes highlights differences in single-nucleotide polymorphisms, structural variations, and transposon composition. Phylogenetic analysis of 5,381 diverse maize and teosinte accessions reveals genetic relationships between sweet corn and other types of maize. Our results show evidence for a common origin in northern Mexico for modern sweet corn in the U.S. Finally, population genomic analysis identifies regions of the genome under selection and candidate genes associated with sweet corn traits, such as early flowering, endosperm composition, plant and tassel architecture, and kernel row number. Our study provides a high-quality reference-genome sequence to facilitate comparative genomics, functional studies, and genomic-assisted breeding for sweet corn.

@article{swarts_joint_2021,
	title = {Joint analysis of days to flowering reveals independent temperate adaptations in maize},
	volume = {126},
	copyright = {2021 The Author(s), under exclusive licence to The Genetics Society},
	issn = {1365-2540},
	url = {https://www.nature.com/articles/s41437-021-00422-z},
	doi = {10.1038/s41437-021-00422-z},
	abstract = {Domesticates are an excellent model for understanding biological consequences of rapid climate change. Maize (Zea mays ssp. mays) was domesticated from a tropical grass yet is widespread across temperate regions today. We investigate the biological basis of temperate adaptation in diverse structured nested association mapping (NAM) populations from China, Europe (Dent and Flint) and the United States as well as in the Ames inbred diversity panel, using days to flowering as a proxy. Using cross-population prediction, where high prediction accuracy derives from overall genomic relatedness, shared genetic architecture, and sufficient diversity in the training population, we identify patterns in predictive ability across the five populations. To identify the source of temperate adapted alleles in these populations, we predict top associated genome-wide association study (GWAS) identified loci in a Random Forest Classifier using independent temperate–tropical North American populations based on lines selected from Hapmap3 as predictors. We find that North American populations are well predicted (AUC equals 0.89 and 0.85 for Ames and USNAM, respectively), European populations somewhat well predicted (AUC equals 0.59 and 0.67 for the Dent and Flint panels, respectively) and that the Chinese population is not predicted well at all (AUC is 0.47), suggesting an independent adaptation process for early flowering in China. Multiple adaptations for the complex trait days to flowering in maize provide hope for similar natural systems under climate change.},
	language = {en},
	number = {6},
	urldate = {2024-03-22},
	journal = {Heredity},
	publisher = {Nature Publishing Group},
	author = {Swarts, Kelly and Bauer, Eva and Glaubitz, Jeffrey C. and Ho, Tiffany and Johnson, Lynn and Li, Yongxiang and Li, Yu and Miller, Zachary and Romay, Cinta and Schön, Chris-Carolin and Wang, Tianyu and Zhang, Zhiwu and Buckler, Edward S. and Bradbury, Peter},
	month = jun,
	year = {2021},
	keywords = {Evolutionary genetics, Quantitative trait},
	pages = {929--941},
}

Domesticates are an excellent model for understanding biological consequences of rapid climate change. Maize (Zea mays ssp. mays) was domesticated from a tropical grass yet is widespread across temperate regions today. We investigate the biological basis of temperate adaptation in diverse structured nested association mapping (NAM) populations from China, Europe (Dent and Flint) and the United States as well as in the Ames inbred diversity panel, using days to flowering as a proxy. Using cross-population prediction, where high prediction accuracy derives from overall genomic relatedness, shared genetic architecture, and sufficient diversity in the training population, we identify patterns in predictive ability across the five populations. To identify the source of temperate adapted alleles in these populations, we predict top associated genome-wide association study (GWAS) identified loci in a Random Forest Classifier using independent temperate–tropical North American populations based on lines selected from Hapmap3 as predictors. We find that North American populations are well predicted (AUC equals 0.89 and 0.85 for Ames and USNAM, respectively), European populations somewhat well predicted (AUC equals 0.59 and 0.67 for the Dent and Flint panels, respectively) and that the Chinese population is not predicted well at all (AUC is 0.47), suggesting an independent adaptation process for early flowering in China. Multiple adaptations for the complex trait days to flowering in maize provide hope for similar natural systems under climate change.

@article{bilinski_parallel_2018,
	title = {Parallel altitudinal clines reveal trends in adaptive evolution of genome size in {Zea} mays},
	volume = {14},
	issn = {1553-7404},
	url = {https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1007162},
	doi = {10.1371/journal.pgen.1007162},
	abstract = {While the vast majority of genome size variation in plants is due to differences in repetitive sequence, we know little about how selection acts on repeat content in natural populations. Here we investigate parallel changes in intraspecific genome size and repeat content of domesticated maize (Zea mays) landraces and their wild relative teosinte across altitudinal gradients in Mesoamerica and South America. We combine genotyping, low coverage whole-genome sequence data, and flow cytometry to test for evidence of selection on genome size and individual repeat abundance. We find that population structure alone cannot explain the observed variation, implying that clinal patterns of genome size are maintained by natural selection. Our modeling additionally provides evidence of selection on individual heterochromatic knob repeats, likely due to their large individual contribution to genome size. To better understand the phenotypes driving selection on genome size, we conducted a growth chamber experiment using a population of highland teosinte exhibiting extensive variation in genome size. We find weak support for a positive correlation between genome size and cell size, but stronger support for a negative correlation between genome size and the rate of cell production. Reanalyzing published data of cell counts in maize shoot apical meristems, we then identify a negative correlation between cell production rate and flowering time. Together, our data suggest a model in which variation in genome size is driven by natural selection on flowering time across altitudinal clines, connecting intraspecific variation in repetitive sequence to important differences in adaptive phenotypes.},
	language = {en},
	number = {5},
	urldate = {2024-03-22},
	journal = {PLOS Genetics},
	publisher = {Public Library of Science},
	author = {Bilinski, Paul and Albert, Patrice S. and Berg, Jeremy J. and Birchler, James A. and Grote, Mark N. and Lorant, Anne and Quezada, Juvenal and Swarts, Kelly and Yang, Jinliang and Ross-Ibarra, Jeffrey},
	month = may,
	year = {2018},
	keywords = {Fish genomics, Inbreeding, Invertebrate genomics, Leaves, Maize, Natural selection, Plant genomics, Transposable elements},
	pages = {e1007162},
}

While the vast majority of genome size variation in plants is due to differences in repetitive sequence, we know little about how selection acts on repeat content in natural populations. Here we investigate parallel changes in intraspecific genome size and repeat content of domesticated maize (Zea mays) landraces and their wild relative teosinte across altitudinal gradients in Mesoamerica and South America. We combine genotyping, low coverage whole-genome sequence data, and flow cytometry to test for evidence of selection on genome size and individual repeat abundance. We find that population structure alone cannot explain the observed variation, implying that clinal patterns of genome size are maintained by natural selection. Our modeling additionally provides evidence of selection on individual heterochromatic knob repeats, likely due to their large individual contribution to genome size. To better understand the phenotypes driving selection on genome size, we conducted a growth chamber experiment using a population of highland teosinte exhibiting extensive variation in genome size. We find weak support for a positive correlation between genome size and cell size, but stronger support for a negative correlation between genome size and the rate of cell production. Reanalyzing published data of cell counts in maize shoot apical meristems, we then identify a negative correlation between cell production rate and flowering time. Together, our data suggest a model in which variation in genome size is driven by natural selection on flowering time across altitudinal clines, connecting intraspecific variation in repetitive sequence to important differences in adaptive phenotypes.

@article{romero_navarro_study_2017,
	title = {A study of allelic diversity underlying flowering-time adaptation in maize landraces},
	volume = {49},
	copyright = {2017 Springer Nature America, Inc.},
	issn = {1546-1718},
	url = {https://www.nature.com/articles/ng.3784},
	doi = {10.1038/ng.3784},
	abstract = {Edward Buckler, Sarah Hearne and colleagues integrate two approaches to characterize the genetic diversity of a large number of geographically distributed maize landraces. They examine flowering time and adaptation to altitude and find that the majority of the associated SNPs overlap both traits.},
	language = {en},
	number = {3},
	urldate = {2024-03-22},
	journal = {Nature Genetics},
	publisher = {Nature Publishing Group},
	author = {Romero Navarro, J. Alberto and Willcox, Martha and Burgueño, Juan and Romay, Cinta and Swarts, Kelly and Trachsel, Samuel and Preciado, Ernesto and Terron, Arturo and Delgado, Humberto Vallejo and Vidal, Victor and Ortega, Alejandro and Banda, Armando Espinoza and Montiel, Noel Orlando Gómez and Ortiz-Monasterio, Ivan and Vicente, Félix San and Espinoza, Armando Guadarrama and Atlin, Gary and Wenzl, Peter and Hearne, Sarah and Buckler, Edward S.},
	month = mar,
	year = {2017},
	keywords = {Plant breeding, Plant genetics},
	pages = {476--480},
}

Edward Buckler, Sarah Hearne and colleagues integrate two approaches to characterize the genetic diversity of a large number of geographically distributed maize landraces. They examine flowering time and adaptation to altitude and find that the majority of the associated SNPs overlap both traits.

@article{swarts_genomic_2017,
	title = {Genomic estimation of complex traits reveals ancient maize adaptation to temperate {North} {America}},
	volume = {357},
	url = {https://www.science.org/doi/10.1126/science.aam9425},
	doi = {10.1126/science.aam9425},
	abstract = {By 4000 years ago, people had introduced maize to the southwestern United States; full agriculture was established quickly in the lowland deserts but delayed in the temperate highlands for 2000 years. We test if the earliest upland maize was adapted for early flowering, a characteristic of modern temperate maize. We sequenced fifteen 1900-year-old maize cobs from Turkey Pen Shelter in the temperate Southwest. Indirectly validated genomic models predicted that Turkey Pen maize was marginally adapted with respect to flowering, as well as short, tillering, and segregating for yellow kernel color. Temperate adaptation drove modern population differentiation and was selected in situ from ancient standing variation. Validated prediction of polygenic traits improves our understanding of ancient phenotypes and the dynamics of environmental adaptation.},
	number = {6350},
	urldate = {2024-03-22},
	journal = {Science},
	publisher = {American Association for the Advancement of Science},
	author = {Swarts, Kelly and Gutaker, Rafal M. and Benz, Bruce and Blake, Michael and Bukowski, Robert and Holland, James and Kruse-Peeples, Melissa and Lepak, Nicholas and Prim, Lynda and Romay, M. Cinta and Ross-Ibarra, Jeffrey and Sanchez-Gonzalez, Jose de Jesus and Schmidt, Chris and Schuenemann, Verena J. and Krause, Johannes and Matson, R. G. and Weigel, Detlef and Buckler, Edward S. and Burbano, Hernán A.},
	month = aug,
	year = {2017},
	pages = {512--515},
}

By 4000 years ago, people had introduced maize to the southwestern United States; full agriculture was established quickly in the lowland deserts but delayed in the temperate highlands for 2000 years. We test if the earliest upland maize was adapted for early flowering, a characteristic of modern temperate maize. We sequenced fifteen 1900-year-old maize cobs from Turkey Pen Shelter in the temperate Southwest. Indirectly validated genomic models predicted that Turkey Pen maize was marginally adapted with respect to flowering, as well as short, tillering, and segregating for yellow kernel color. Temperate adaptation drove modern population differentiation and was selected in situ from ancient standing variation. Validated prediction of polygenic traits improves our understanding of ancient phenotypes and the dynamics of environmental adaptation.

@article{takuno_independent_2015,
	title = {Independent {Molecular} {Basis} of {Convergent} {Highland} {Adaptation} in {Maize}},
	volume = {200},
	issn = {1943-2631},
	url = {https://doi.org/10.1534/genetics.115.178327},
	doi = {10.1534/genetics.115.178327},
	abstract = {Convergent evolution is the independent evolution of similar traits in different species or lineages of the same species; this often is a result of adaptation to similar environments, a process referred to as convergent adaptation. We investigate here the molecular basis of convergent adaptation in maize to highland climates in Mesoamerica and South America, using genome-wide SNP data. Taking advantage of archaeological data on the arrival of maize to the highlands, we infer demographic models for both populations, identifying evidence of a strong bottleneck and rapid expansion in South America. We use these models to then identify loci showing an excess of differentiation as a means of identifying putative targets of natural selection and compare our results to expectations from recently developed theory on convergent adaptation. Consistent with predictions across a wide parameter space, we see limited evidence for convergent evolution at the nucleotide level in spite of strong similarities in overall phenotypes. Instead, we show that selection appears to have predominantly acted on standing genetic variation and that introgression from wild teosinte populations appears to have played a role in highland adaptation in Mexican maize.},
	number = {4},
	urldate = {2024-03-22},
	journal = {Genetics},
	author = {Takuno, Shohei and Ralph, Peter and Swarts, Kelly and Elshire, Rob J and Glaubitz, Jeffrey C and Buckler, Edward S and Hufford, Matthew B and Ross-Ibarra, Jeffrey},
	month = aug,
	year = {2015},
	pages = {1297--1312},
}

Convergent evolution is the independent evolution of similar traits in different species or lineages of the same species; this often is a result of adaptation to similar environments, a process referred to as convergent adaptation. We investigate here the molecular basis of convergent adaptation in maize to highland climates in Mesoamerica and South America, using genome-wide SNP data. Taking advantage of archaeological data on the arrival of maize to the highlands, we infer demographic models for both populations, identifying evidence of a strong bottleneck and rapid expansion in South America. We use these models to then identify loci showing an excess of differentiation as a means of identifying putative targets of natural selection and compare our results to expectations from recently developed theory on convergent adaptation. Consistent with predictions across a wide parameter space, we see limited evidence for convergent evolution at the nucleotide level in spite of strong similarities in overall phenotypes. Instead, we show that selection appears to have predominantly acted on standing genetic variation and that introgression from wild teosinte populations appears to have played a role in highland adaptation in Mexican maize.

@article{swarts_novel_2014,
	title = {Novel {Methods} to {Optimize} {Genotypic} {Imputation} for {Low}-{Coverage}, {Next}-{Generation} {Sequence} {Data} in {Crop} {Plants}},
	volume = {7},
	copyright = {© 2014 The Authors.},
	issn = {1940-3372},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.3835/plantgenome2014.05.0023},
	doi = {10.3835/plantgenome2014.05.0023},
	abstract = {Next-generation sequencing technology such as genotyping-by-sequencing (GBS) made low-cost, but often low-coverage, whole-genome sequencing widely available. Extensive inbreeding in crop plants provides an untapped, high quality source of phased haplotypes for imputing missing genotypes. We introduce Full-Sib Family Haplotype Imputation (FSFHap), optimized for full-sib populations, and a generalized method, Fast Inbred Line Library ImputatioN (FILLIN), to rapidly and accurately impute missing genotypes in GBS-type data with ordered markers. FSFHap and FILLIN impute missing genotypes with high accuracy in GBS-genotyped maize (Zea mays L.) inbred lines and breeding populations, while Beagle v. 4 is still preferable for diverse heterozygous populations. FILLIN and FSFHap are implemented in TASSEL 5.0.},
	language = {en},
	number = {3},
	urldate = {2024-03-22},
	journal = {The Plant Genome},
	author = {Swarts, Kelly and Li, Huihui and Romero Navarro, J. Alberto and An, Dong and Romay, Maria Cinta and Hearne, Sarah and Acharya, Charlotte and Glaubitz, Jeffrey C. and Mitchell, Sharon and Elshire, Robert J. and Buckler, Edward S. and Bradbury, Peter J.},
	year = {2014},
	note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.3835/plantgenome2014.05.0023},
	pages = {plantgenome2014.05.0023},
}

Next-generation sequencing technology such as genotyping-by-sequencing (GBS) made low-cost, but often low-coverage, whole-genome sequencing widely available. Extensive inbreeding in crop plants provides an untapped, high quality source of phased haplotypes for imputing missing genotypes. We introduce Full-Sib Family Haplotype Imputation (FSFHap), optimized for full-sib populations, and a generalized method, Fast Inbred Line Library ImputatioN (FILLIN), to rapidly and accurately impute missing genotypes in GBS-type data with ordered markers. FSFHap and FILLIN impute missing genotypes with high accuracy in GBS-genotyped maize (Zea mays L.) inbred lines and breeding populations, while Beagle v. 4 is still preferable for diverse heterozygous populations. FILLIN and FSFHap are implemented in TASSEL 5.0.

@book{swarts_structural_2012,
	address = {Center for Desert Archaeology},
	series = {Anthropological {Papers}},
	title = {Structural {Wood} {Choice} and {Cultural} {Meaning} at {Honey} {Bee} {Village}. {Life} in the valley of gold, archaeological investigations at {Honey} {Bee} {Village}, a prehistoric {Hohokam} ballcourt village in the {Canada} del {Oro} {Valley} of southern {Arizona}: introduction, chronology, material culture investigations and research results.},
	shorttitle = {Life in the {Valley} of {Gold}},
	abstract = {Honey Bee Village was a sizeable prehistoric Hohokam village complete with a plaza, mounds, and ballcourt located in the Cañada del Oro Valley north of Tucson, Arizona. In 2006 and 2007, nearly three-quarters of the village was intensively excavated under contract with Pima County and Vistoso Partners. The core of the site is a 13-acre preserve that was tested in the 1980s. Outside the core area, the full plan of the village was revealed, resulting in the identification of 2,004 cultural features. Occupation ranged from late in the Tortolita phase to the early Tanque Verde phase, roughly A.D. 650-1200. Overall, 947 cultural features were fully or partially excavated, including 183 pit structures, possible structures, and adobe rooms, 207 human burial features, 11 animal burials, 24 trash mounds or concentrations, and 522 extramural features. Particularly interesting remains uncovered include a golden eagle burial and a Late Rincon phase plaza and plaza cemetery. The wide excavation coverage permitted an unusually complete view of a Hohokam village and of surface-subsurface comparisons.

The archaeological features and artifacts recovered are documented in this two-volume report. A large set of radiocarbon and archaeomagnetic dates is discussed. Household economic specialization and architectural practices are addressed. Cremation mortuary practices are reconstructed, and Hohokam perspectives on death and the dead are considered. The history and shifting settlement structure of the village are considered in relation to its nearby sister village, Sleeping Snake. Of special interest is the discovery that logs obtained from the Santa Catalina Mountains were used in house construction.},
	language = {en-US},
	urldate = {2024-03-22},
	publisher = {Archaeology Southwest},
	author = {Swarts, Kelly},
	month = jun,
	year = {2012},
	note = {Edited by Henry D. Wallace},
}

Honey Bee Village was a sizeable prehistoric Hohokam village complete with a plaza, mounds, and ballcourt located in the Cañada del Oro Valley north of Tucson, Arizona. In 2006 and 2007, nearly three-quarters of the village was intensively excavated under contract with Pima County and Vistoso Partners. The core of the site is a 13-acre preserve that was tested in the 1980s. Outside the core area, the full plan of the village was revealed, resulting in the identification of 2,004 cultural features. Occupation ranged from late in the Tortolita phase to the early Tanque Verde phase, roughly A.D. 650-1200. Overall, 947 cultural features were fully or partially excavated, including 183 pit structures, possible structures, and adobe rooms, 207 human burial features, 11 animal burials, 24 trash mounds or concentrations, and 522 extramural features. Particularly interesting remains uncovered include a golden eagle burial and a Late Rincon phase plaza and plaza cemetery. The wide excavation coverage permitted an unusually complete view of a Hohokam village and of surface-subsurface comparisons. The archaeological features and artifacts recovered are documented in this two-volume report. A large set of radiocarbon and archaeomagnetic dates is discussed. Household economic specialization and architectural practices are addressed. Cremation mortuary practices are reconstructed, and Hohokam perspectives on death and the dead are considered. The history and shifting settlement structure of the village are considered in relation to its nearby sister village, Sleeping Snake. Of special interest is the discovery that logs obtained from the Santa Catalina Mountains were used in house construction.