Biology subjects

Schmid, K. J.

Publications and source records attributed to Schmid, K. J..

18 recordsLinked to original sources

bioRxiv2026

Leveraging genome-wide association studies and genomic prediction for distinctness, uniformity, and stability (DUS) testing in maize

Testing for distinctness, uniformity, and stability (DUS) is a requirement for plant variety registration and based on phenotypic traits, which is time-consuming and sensitive to environmental variation. Advances in genomics allow to complement DUS testing with molecular markers, for which two models in DUS testing were proposed by the Union for the Protection of New Varieties of Plants (UPOV). A use cases was described for maize, but an implementation has been hindered by a lack of suitable markers and validated analytical frameworks. We address these challenges by integrating historical DUS characteristics scores from 352 European hybrid maize varieties with high-density genome-wide single nucleotide polymorphism (SNP) data. Using genome-wide association studies (GWAS), we identified 18 genomic regions and candidate genes associated with 12 DUS characteristics, enabling the development of diagnostic markers consistent with the UPOV model "Characteristic-Specific Molecular Markers". Since most DUS traits are polygenic, we combined GWAS-informed marker selection with XG-Boost-based machine learning to predict notes of DUS characteristics. This approach achieved strong predictive performance across multiple traits (mean accuracy 0.67), demonstrating its potential for managing reference collections under UPOV model "Combining phenotypic and molecular distances in the management of variety collections". Both approaches were validated for two characteristics using independent public USDA-NPGS maize datasets (>1,700 accessions) highlighting the value of public data for method validation. We also identify key limitations of historical DUS data, including imbalanced and sparse trait representation, and discuss mitigation strategies. Despite these constraints, our results demonstrate that molecular markers may improve maize DUS testing, enabling faster, more accurate variety registration and supporting accelerated crop improvement. Key messageHistorical DUS datasets can be used to identify marker-trait associations of DUS characteristics using genome-wide association study (GWAS) and to develop a genomic prediction framework for an accurate prediction of DUS character notes from marker data.

genetics↗

bioRxiv2026

Phenotypic differentiation between highland and coastal quinoa under cold stress conditions

Quinoa (Chenopodium quinoa Willd.) is a genetically diverse Andean crop valued for its nutrition and adaptability to varied agro-climatic conditions with potential for cultivation in European and Mediterranean, particularly on marginal lands. Low temperatures during early sowing can impair germination, while delayed sowing increases the risk of poor maturation due to unfavorable autumn weather. To assess the adaptation of quinoa to low temperature conditions, that reflect cold stress, we evaluated germination and phenotypic variation in 60 accessions from highland and coastal ecotypes across three sowing dates in South-Western Germany: late winter (S1), early spring (S2), and spring (S3). Early sowing under low temperature conditions in S1 delayed seedling-emergence and reduced emergence percentages, yet these plants produced the highest average seed yield per plot (64 g) compared to S2 (46 g) and S3 (35 g). Highland accessions showed earlier seedling-emergence and with higher emergence percentages, while coastal types matured earlier and gave higher yields across sowing dates. A complementary laboratory experiment assessed germination under cold (4.4 {degrees}C) and control (18.3 {degrees}C) conditions, using both manual scoring and image analysis via a Mask R Convolutional Neural Network, to track seedling growth. This confirmed the beneficial germination performance of highland accessions under low temperature conditions, with strong agreement between manual and automated scoring. Our findings suggest that quinoa demonstrates resilience to cold stress with highland quinoa exhibiting superior germination traits, and early sowing, despite reduced emergence, can lead to higher yields. We conclude that combining favorable traits such as faster maturity and higher yield of coastal ecotypes with superior germination traits of highland accessions is a promising avenue for breeding improved quinoa varieties for cold climatic regions.

plant biology↗

bioRxiv2025

Rapid replacement of established by exotic genetic lineages of the fungal maize pathogen Exserohilum turcicum in the Swiss Rhine valley

The fungal maize pathogen Exserohilum turcicum, the causative agent of Northern Corn Leaf Blight (NCLB) was introduced to Europe in the late 19th century, E. turcicum where it rapidly expanded. It persisted in four major clonal lineages and multiple physiological races, defined by their interactions with maize disease resistance genes. In a metagenomic survey of natural infections on the susceptible traditional landrace Rheintaler Ribelmais in the Swiss Rhine Valley during 2016 and 2017, we found that one of these clonal lineages ( Small clonal cluster) was dominant in the region. We repeated the surveys in subsequent years and applied a novel pooling strategy to facilitate large-scale sampling by combining ten infected leaves per sampling location. This approach increased sample throughput while reducing sequencing and laboratory costs. The new survey revealed in 2021 and 2022 a significant temporal shift in population structure of exotic genetic lineages from the tropical Kenyan cluster, which have become predominant. It indicates recent introduction and establishment of genetically diverse, tropical E. turcicum lineages into a temperate agricultural system, possibly facilitated by climate change and global seed exchange. Phyllobiome analyses of infected leaves showed that microbial community composition varied across years but remained largely consistent between maize variety types (landrace vs. hybrid). Overall, metagenomic pool sequencing of infected leaves proves to be a cost-effective, spatially resolved method for pathogen monitoring and provides useful evidence for the evolving epidemiology of E. turcicum, with implications for developing durable resistance in maize breeding programs.

plant biology↗

bioRxiv2025

Effects of using deep learning to predict the geographic origin of barley genebank accessions on genome-environment association studies

AbstractGenome-environment association (GEA) is an approach for identifying adaptive loci by combining genetic variation with environmental parameters, offering potential for improving crop resilience. However, its application to genebank accessions is limited by missing geographic origin data. To address this limitation, we explored the use of neural networks to predict the geographic origins of barley accessions and integrate imputed environmental data into GEA. Neural networks demonstrated high accuracy in cross-validation but occasionally produced ecologically implausible predictions as models solely considered geographical proximity. For example, some predicted origins were located within non-arable regions, such as the Mediterranean Sea. Using barley flowering time genes as benchmarks, GEA integrating imputed environmental data (N=11,032) displayed partially concordant yet complementary detection of genomic regions near flowering time genes compared to regular GEA (N=1,626), highlighting the potential of GEA with imputed data to complement regular GEA in uncovering novel adaptive loci. Also, contrary to our initial hypothesis anticipating a significant improvement in GEA performance by increasing sample size, our simulations yield unexpected insights. Our study suggests potential limitations in the sensitivity of GEA approaches to the considerable expansion in sample size achieved through predicting missing geographical data. Overall, our study provides insights into leveraging incomplete geographical origin data by integrating deep learning with GEA. Our findings indicate the need for further development of GEA approaches to optimize the use of imputed environmental data, such as incorporating regional GEA patterns instead of solely focusing on global associations between allele frequencies and environmental gradients across large-scale landscapes.

plant biology↗

bioRxiv2024

Regional Diversity and Leaf Microbiome Interactions of the Fungal Maize Pathogen Exserohilum turcicum in Switzerland: AMetagenomic Analysis

The spread and adaptation of fungal plant pathogens in agroecosystems are facilitated by environmental homogeneity. Metagenomic sequencing of infected tissues allows to monitor eco-evolutionary dynamics and interactions betwen host, pathogen and the plant microbiome. Exserohilum turcicum, the causal agent of northern corn leaf blight (NCLB) in maize, is distributed in multiple clonal lineages throughout Europe. To characterize regional pathogen diversity, we conducted metagenomic DNA sequencing on 241 infected leaf samples from the highly susceptible Swiss maize landrace Rheintaler Ribelmais, collected over three years (2016-2018) from an average of 14 agricultural farms within the Swiss Rhine Valley. All major European clonal lineages of E. turcicum were identified. Lineages differ by their mating types which indicates potential for sexual recombination and rapid evolution of new pathogen strains, although we found no evidence of recent recombination. The associated eukaryotic and prokaryotic leaf microbiome exhibited variation in taxonomic diversity between years and locations and is likely influenced by local weather conditions. A network analysis revealed distinct clusters of eukaryotic and prokaryotic taxa that correlates with the frequency of E. turcicum sequencing reads, suggesting causal interactions. Notably, the yeast genus Metschnikowia exhibited a strongly negative correlation, supporting its known potential as biological control agent against fungal pathogens. Our findings show that metagenomic sequencing is a useful tool for analyzing the role of environmental factors and potential pathogen-microbiome interactions in shaping pathogen dynamics and evolution, suggesting their potential for effective pathogen management strategies.

plant biology↗

bioRxiv2022

High-density mapping of QTL controlling agronomically important traits in quinoa (Chenopodium quinoa Willd.)

Quinoa is a pseudocereal originating from the Andean regions. In spite of quinoas long cultivation history, genetic analysis of this crop is still in its infancy. We aimed to localize QTL contributing to the phenotypic variation of agronomically important traits. We crossed the Chilean accession PI-614889 and the Peruvian accession CHEN-109, which depicted significant differences in days to flowering, days to maturity, plant height, panicle length, thousand kernel weight (TKW), saponin content, and mildew susceptibility. We observed sizeable phenotypic variation across F2 plants and F3 families grown in the greenhouse and in the field, respectively. We used Skim-seq to genotype the F2 population and constructed a high-density genetic map with 133,923 SNPs. Fifteen QTL were found for ten traits. Two significant QTL, common in F2 and F3 generations, depicted pleiotropy for days to flowering, plant height, and TKW. The pleiotropic QTL harbored several putative candidate genes involved in photoperiod response and flowering time regulation. This study presents the first high-density genetic map of quinoa that incorporates QTL for several important agronomical traits. The pleiotropic loci can facilitate marker assisted selection in quinoa breeding programs. Key messageSkim-sequencing enabled the construction a high-density genetic map (133,923 SNPs) and fifteen QTL were detected for ten agronomically important traits.

genetics↗

bioRxiv2022

Using landscape genomics to infer genomic regions involved in environmental adaptation of soybean genebank accessions

Understanding how crops adapt to specific environmental conditions is becoming increasingly important in the face of accelerating climate change, but the genetics of local adaptation remain little understood for many crops. Landscape genomics can reveal patterns of genetic variation that indicate adaptive diversification during crop evolution and dispersal. Here, we examine genetic differentiation and association signatures with environmental gradients in soybean (Glycine max) germplasm groups from China that were inferred from the USDA Soybean Germplasm Collection (N = 17,019 accessions) based on population structure and passport information. We recover genes previously known to be involved in soybean environmental adaptation and report numerous new candidate genes in selection signatures implicated by genomic resources such as the genome annotation and gene expression datasets to function in flowering regulation, photoperiodism and stress reaction cascades. Linkage disequilibrium network analysis suggested functional relationships between genomic regions with selection signatures, consistent with the polygenic nature of environmental adaptation. We tested whether haplotypes associated with environmental adaptation in China were present in 843 North American and 160 European soybean cultivars and found that haplotypes in major genes for early maturity have been selected during breeding, but also that a large number of haplotypes exhibiting putative adaptive variation for cold regions at high latitudes are underrepresented in modern cultivars. Our results demonstrate the value of landscape genomics analysis in genebank germplasm as a starting point for the study of crop environmental adaptation and have the potential to inform future research efforts focused on improved soybean adaptation. Functional validation of candidate genes will support understanding of their adaptive roles and likely enable the transfer of beneficial adaptive variation into modern breeding germplasm.

plant biology↗

bioRxiv2021

Parental environmental effects are common and strong, but unpredictable, in Arabidopsis thaliana

The phenotypes of plants can be influenced by the environmental conditions experienced by their parents. In some cases, such parental effects have been found to be adaptive, which has led to much speculation about their ecological and evolutionary significance. However, there is still much uncertainty about how common and how predictable parental environmental effects really are. We carried out a comprehensive test for parental effects of different environmental stresses in the model plant Arabidopsis thaliana. We subjected plants of three Arabidopsis genotypes to a broad range of biotic or abiotic stresses, or combinations thereof, and compared their offspring phenotypes in a common environment. The majority of environmental stresses (16 out of 24 stress treatments) caused significant parental effects, in particular on plant biomass and reproduction, with positive or negative effects ranging from -35% to +38% changes in offspring fitness. The expression of parental effects was strongly genotype-dependent, with some effects only present in some genotypes but absent, or even in the opposite direction, in others. Parental effects of multiple environmental stresses were often non-additive, and their effects can thus not be predicted from what we know about the effects of individual stresses. Intriguingly, the direction and magnitude of parental effects were unrelated to the direct effects on the parents: some stresses did not affect the parents but caused substantial effects on offspring, while for others the situation was reversed. In summary, parental environmental effects are common and often strong in A. thaliana, but they are genotype-dependent and difficult to predict. SignificanceStress experienced by plants can alter the phenotypes of their offspring. To understand the ecological and evolutionary significance of such parental effects, we must know how common and how predictable they are. In a large experiment with Arabidopsis thaliana, we show that the majority of 24 environmental stresses cause significant, and often strong, positive or negative parental effects. However, we also find that parental effects are genotype-specific and unrelated to the direct effect of individual stresses, and that multiple stresses often act in non-additive ways across generations. Thus, parental effects appear to be common and strong, but difficult to predict. Our findings have important implications for the study of plant responses to environmental change, and the design of stress experiments.

ecology↗

bioRxiv2021

Physical geography, isolation by distance and environmental variables shape genomic variation of wild barley (Hordeum vulgare L. ssp. spontaneum in the Southern Levant

Determining the extent of genetic variation that reflects local adaptation in crop wild relatives is of interest to discovering useful genetic diversity for plant breeding. We investigated the association of genomic variation with geographical and environmental factors in wild barley (Hordeum vulgare L. ssp. spontaneum) populations of the Southern Levant using genotyping-by-sequencing (GBS) of 244 accessions of the Barley1K+ collection. Inference of population structure resulted in four genetic clusters that corresponded to eco-geographical habitats and a significant association of lower gene flow rates with geographical barriers, e.g. the Judaean Mountains and the Sea of Galilee. Redundancy analysis (RDA) revealed that spatial autocorrelation explained 45% and environmental variables explained 15% of total genomic variation. Only 4.5% of genomic variation was exclusively attributed to environmental variation if the component confounded with spatial autocorrelation was excluded. A synthetic environmental variable combining latitude, solar radiation, and accumulated precipitation explained the highest proportion of genomic variation (3.9%). After correcting for population structure, soil water capacity was the most important environmental variable explaining 1.18% of genomic variation. Genome scans with outlier analysis and genome-environment association studies were conducted to identify signatures of adaptation. RDA and outlier methods jointly detected selection signatures in the pericentromeric regions of chromosome 3H, 4H, and 5H, but they mostly disappeared after correction for population structure. In conclusion, adaptation to the highly diverse environments of the Southern Levant over short geographical ranges has a small effect on the genomic diversity of wild barley highlighting the importance of non-selective forces in genetic differentiation.

evolutionary biology↗

bioRxiv2021

DeepCob: Precise and high-throughput analysis of maize cob geometry using deep learning with an application in genebank phenomics

BackgroundMaize cobs are an important component of crop yield that exhibit a high diversity in size, shape and color in native landraces and modern varieties. Various phenotyping approaches were developed to measure maize cob parameters in a high throughput fashion. More recently, deep learning methods like convolutional neural networks (CNN) became available and were shown to be highly useful for high-throughput plant phenotyping. We aimed at comparing classical image segmentation with deep learning methods for maize cob image segmentation and phenotyping using a large image dataset of native maize landrace diversity from Peru. ResultsComparison of three image analysis methods showed that a Mask R-CNN trained on a diverse set of maize cob images was highly superior to classical image analysis using the Felzenszwalb algorithm and a Window-based CNN due to its robustness to image quality and object segmentation accuracy (r = 0.99). We integrated Mask R-CNN into a high-throughput pipeline to segment both maize cobs and rulers in images and perform an automated quantitative analysis of eight phenotypic traits, including diameter, length, ellipticity, asymmetry, aspect ratio and average RGB values for cob color. Statistical analysis identified key training parameters for efficient iterative model updating. We also show that a small number of 10-20 images is sufficient to update the initial Mask R-CNN model to process new types of cob images. To demonstrate an application of the pipeline we analyzed phenotypic variation in 19,867 maize cobs extracted from 3,449 images of 2,484 accessions from the maize genebank of Peru to identify phenotypically homogeneous and heterogeneous genebank accessions using multivariate clustering. ConclusionsSingle Mask R-CNN model and associated analysis pipeline are widely applicable tools for maize cob phenotyping in contexts like genebank phenomics or plant breeding.

plant biology↗

bioRxiv2020

Population history of the Northern corn leaf blight fungal pathogen Setosphaeria turcica in Europe

Modern agricultural practices and the climate change foster the rapid spread of plant pathogens like the maize fungal pathogen Setosphaeria turcica, which causes Northern corn leaf blight and expanded into Central Europe since the 1980s. To investigate the rapid expansion of S. turcica we sequenced 121 isolates from Europe and Kenya. Population genomic inference revealed a single genetically diverse cluster in Kenya and three clonal lineages with low diversity and one cluster of multiple clonal sublineages in Europe. Phylogenetic dating suggests that all European lineages originated by sexual reproduction outside Europe and subsequently were subsequently introgressed multiple times. In contrast to Kenyan isolates, European isolates did not show sexual recombination despite the presence of both MAT1-1 and MAT1-2 mating types. Coalescent analysis of the geographically most widespread European lineage supported a neutral, strongly exponential population growth model over models with natural selection caused by host defence resistance or environmental adaptation. Within clonal lineages, we observed phenotypic variation in virulence to different monogenic resistances that may originate from repeated mutations in virulence genes. Association mapping between genetic clusters did not identify genomic regions associated with pathogen races but uncovered strongly differentiated genomic regions between clonal lineages that harbor putative effector genes. In conclusion, the expansion and population growth of S. turcica in Europe was mainly driven by the expansion of maize cultivation area and not by rapid adaptation. Significance statementThe geographic expansion and plant pathogens caused by modern agricultural practices and climate change is a major problem in modern agriculture. We investigated the rapid spread of the maize fungal pathogen Setosphaeria turcica by whole genome sequencing of isolates from Kenya and Europe and demonstrated that the rapid expansion in Central Europe since the 1980s mainly reflects the rapid growth of the maize cultivation area in this region and not a rapid adaptation to resistant maize varieties. Our analyses show that by monitoring whole genome sequence diversity of plant pathogens and their invasion history, agricultural management and breeding strategies can be developed to control the evolution and future spread of plant pathogens.

evolutionary biology↗

bioRxiv2020

Genetic variation for tolerance to the downy mildew pathogen Peronospora variabilis in genetic resources of quinoa (Chenopodium quinoa)

BackgroundQuinoa (Chenopodium quinoa Willd.) is an ancient grain crop that is tolerant to abiotic stress and has favorable nutritional properties. Downy mildew is the main disease of quinoa and is caused by infections of the biotrophic oomycete Peronospora variabilis Gaum. Since the disease causes major yield losses, identifying sources of downy mildew tolerance in genetic resources and understanding its genetic basis are important goals in quinoa breeding. ResultsWe infected 132 South American genotypes, three Danish cultivars and the weedy relative C. album with a single isolate of P. variabilis under greenhouse conditions and observed a large variation in disease traits like severity of infection, which ranged from 5% to 83%. Linear mixed models revealed a significant effect of genotypes on disease traits with high heritabilities (0.72 to 0.81). Factors like altitude at site of origin or seed saponin content did not correlate with mildew tolerance, but stomatal width was weakly correlated with severity of infection. Despite the strong genotypic effects on mildew tolerance, genome-wide association mapping with 88 genotypes failed to identify significant marker-trait associations indicating a polygenic architecture of mildew tolerance. ConclusionsThe strong genetic effects on mildew tolerance allow to identify genetic resources, which are valuable sources of resistance in future quinoa breeding.

plant biology↗

bioRxiv2019

Combining Focused Identification of Germplasm and Core Collection Strategies to Identify Genebank Accessions for Central European Soybean Breeding

Environmental adaptation of crops is essential for reliable agricultural production and an important breeding objectives. Genbanks provide genetic variation for the improvement of modern varieties, but the selection of suitable germplasm is frequently impeded by incomplete phenotypic data. We address this bottleneck by combining a Focused Identification of Germplasm Strategy (FIGS) with core collection methodology to select soybean (Glycine max) germplasm for Central European breeding from a collection of >17,000 accessions. By focussing on environmental adaptation to high-latitude cold regions, we selected an environmental precore of 3,663 accessions using environmental data and compared the Donor Population of Environments (DPE) in Asia and the Target Population of Environments (TPE) in Central Europe in the present and in 2070. Using SNP genotypes we reduced the precore into two diverse core collections of 183 and 366 of accessions as diversity panels for evaluation in high-latitude cold regions. Tests of genetic differentiation between precore and core collections revealed differentiation signatures in genomic regions that control maturity, and novel candidate loci for environmental adaptation demonstrating the potential of diversity panels for studying environmental adaptation. Objective-driven core collections increase germplasm utilization for abiotic adaptation by breeding for a rapidly changing climate, or de novo adaptation of crop species to expand cultivation ranges.

plant biology↗

bioRxiv2019

Convergent seed color adaptation during repeated domestication of an ancient new world grain

Out of the almost 2,000 plants that have been selected as crops, only few are fully domesticated, and many intermediates between wild plants and domesticates exist. Genetic constraints might be the reason why incompletely domesticated plants have few characteristic crop traits, and retained numerous wild plant features. Here, we investigate the incomplete domestication of an ancient grain from the Americas, amaranth. We sequenced 121 genomes of the crop and its wild ancestors to show that grain amaranth has been selected three times independently from a single wild ancestor, but has not been fully domesticated. Our analysis identified a MYB-like transcription factor gene as key regulator for seed color variation and shows that the trait was independently converted in Central and South America. We suggest a low effective population size at the time of domestication as potential cause for the lack of adaptation of complex domestication traits. Our results show how genetic constraints influenced domestication and might have set the fate of hundreds of crops.

evolutionary biology↗

bioRxiv2019

Microclimate predicts frost-hardiness of alpine Arabidopsis thaliana populations better than altitude because the microclimate effect increases with altitude

O_LIIn mountain regions average temperatures decrease at higher altitudes. In addition, microenvironmental conditions can strongly affect microclimate and may counteract average effects of altitude. C_LIO_LIWe investigated winter frost hardiness of Arabidopsis thaliana accessions originating from 13 sites along altitudinal gradients in the Southern Alps during three winters on an experimental field station on the Swabian Jura and compared levels of frost damage with the observed number of frost days (<1{degrees}C) in eight collection sites. C_LIO_LIWe found that frost-hardiness increased with altitude in a log-linear fashion. This is consistent with adaptation to higher frequency of frost conditions, but also indicates a decreasing rate of change in frost hardiness with increasing altitude. Moreover, the number of frost days measured with temperature loggers at the original collection sites correlated much better with frost-hardiness than the altitude of collection sites, suggesting that populations were adapted to their local microclimate. Notably, the variance in frost days across sites increased exponentially with altitude. C_LIO_LITogether, our results suggest that strong microclimate heterogeneity of high alpine environments may preserve functional genetic diversity in small populations. This challenges the suitability of habitat predictions based on large scale climatic variables (or proxies, such as altitude) for topographically complex areas. C_LI

evolutionary biology↗

bioRxiv2018

Thermal plasticity of the circadian clock is under nuclear and cytoplasmic control in wild barley

Temperature compensation, expressed as the ability to maintain clock characteristics (mainly period) in face of temperature changes, is considered a key feature of circadian clock systems. In this study, we explore the genetic basis for circadian clock plasticity under high temperatures by utilizing a new doubled haploid (DH) population derived from two reciprocal Hordeum vulgare sps. spontaneum hybrids genotypes (crosses between B1K-50-04 and B1K-09-07). Genotyping by sequencing of DH lines indicated a rich recombination landscape, with minor fixation (less than 8%), for one of the parental alleles, yet with prevalent and varied segregation distortion across seven barley chromosomes. Phenotyping was conducted with a high-throughput platform under optimal and high temperature environments. Genetic analysis, which included QxE and binary-threshold models, identified a significant influence of the maternal organelle genome (the plasmotype), as well as several nuclear quantitative trait loci (QTL), on clock phenotypes (free-running period and amplitude). Moreover, it showed the differential contribution of cytoplasmic genome clock rhythm buffering against high temperature. Resequencing of the parental chloroplast indicated the presence of several candidate genes underlying these significant effects. This first reported plasmotype-driven clock plasticity paves the way for identifying an hitherto unknown impact of nuclear and plasmotype variations on clock robustness and on plant adaptation to changing environments.\n\nHighlightCircadian clock robustness to high temperature is controlled by nuclear and plasmotype quantitative trait loci in a wild barley (Hordeum vulgare ssp. spontaneum) reciprocal doubled haploid population.

genetics↗

bioRxiv2017

Comparative analysis of genetic diversity and differentiation of cauliflower (Brassica oleracea var. botrytis) accessions from two ex situ genebanks

Cauliflower (Brassica oleracea var. botrytis) is an important vegetable crop for human nutrition. We characterized 192 cauliflower accessions from the USDA and IPK genebanks with genotyping by sequencing (GBS). They originated from 26 different countries and represent about 44% of all cauliflower accessions in both genebanks. The analysis of genetic diversity revealed that accessions formed two major groups that represented the two genebanks and were not related to the country of origin. This differentiation was robust with respect to the analysis methods that included principal component analysis, ADMIXTURE and neighbor-joining trees. Genetic diversity was higher in the USDA collection and significant phenotypic differences between the two genebanks were found in three out of six traits investigated. GBS data have a high proportion of missing data, but we observed that the exclusion of single nucleotide polymorphisms (SNPs) with missing data or the imputation of missing SNP alleles produced very similar results. The results indicate that the composition and type of accessions have a strong effect on the structure of genetic diversity of ex situ collections, although regeneration procedures and local adaptation to regeneration conditions may also contribute to a divergence. Fst-based outlier tests of genetic differentiation identified only a small proportion (<1%) of SNPs that are highly differentiated between the two genebanks, which indicates that selection during seed regeneration is not a major cause of differentiation between genebanks. Seed regeneration procedures of both genebanks do not result in different levels of genetic drift and loss of genetic variation. We therefore conclude that the composition and type of accessions mainly influence the level of genetic diversity and explain the strong genetic differentiation between the two ex situ collections. In summary, GBS is a useful method for characterizing genetic diversity in cauliflower genebank material and our results suggest that it may be useful to incorporate routine genotyping into accession management and seed regeneration to monitor the diversity present in ex situ collections and to reduce the loss of genetic diversity during seed regeneration.

plant biology↗

bioRxiv2016

Phylogenetic relationships and genome size evolution within the genus Amaranthus indicate the ancestors of an ancient crop

The genus Amaranthus consists of 50 to 70 species and harbors several cultivated and weedy species of great economic importance. A small number of suitable traits, phenotypic plasticity, gene flow and hybridization made it difficult to establish the taxonomy and phylogeny of the whole genus despite various studies using molecular markers. We inferred the phylogeny of the Amaranthus genus using genotyping by sequencing (GBS) of 94 genebank accessions representing 35 Amaranthus species and measured their genome sizes. SNPs were called by de novo and reference-based methods, for which we used the distant sugarbeet Beta vulgaris and the closely related Amaranthus hypochondriacus as references. SNP counts and proportions of missing data differed between methods, but the resulting phylogenetic trees were highly similar. A distance-based neighbor joing tree of individual accessions and a species tree calculated with the multispecies coalescent supported a previous taxonomic classification into three subgenera although the subgenus A. Acnida consists of two highly differentiated clades. The analysis of the Hybridus complex within the A. Amaranthus subgenus revealed insights on the history of cultivated grain amaranths. The complex includes the three cultivated grain amaranths and their wild relatives and was well separated from other species in the subgenus. Wild and cultivated amaranth accessions did not differentiate according to the species assignment but clustered by their geographic origin from South and Central America. Different geographically separated populations of Amaranthus hybridus appear to be the common ancestors of the three cultivated grain species and A. quitensis might be additionally be involved in the evolution of South American grain amaranth (A. caudatus). We also measured genome sizes of the species and observed little variation with the exception of two lineages that showed evidence for a recent polyploidization. With the exception of two lineages, genome sizes are quite similar and indicate that polyploidization did not play a major role in the history of the genus.

evolutionary biology↗