Genome-wide identification and expression analysis of the SET domain-containing gene family in potato (Solanum tuberosum L.)

Genes containing the SET domain can catalyse histone lysine methylation, which in turn has the potential to cause changes to chromatin structure and regulation of the transcription of genes involved in diverse physiological and developmental processes. However, the functions of SET domain-containing (StSET) genes in potato still need to be studied. The objectives of our study can be summarized as in silico analysis to (i) identify StSET genes in the potato genome, (ii) systematically analyse gene structure, chromosomal distribution, gene duplication events, promoter sequences, and protein domains, (iii) perform phylogenetic analyses, (iv) compare the SET domain-containing genes of potato with other plant species with respect to protein domains and orthologous relationships, (v) analyse tissue-specific expression, and (vi) study the expression of StSET genes in response to drought and heat stresses. In this study, we identified 57 StSET genes in the potato genome, and the genes were physically mapped onto eleven chromosomes. The phylogenetic analysis grouped these StSET genes into six clades. We found that tandem duplication through sub-functionalisation has contributed only marginally to the expansion of the StSET gene family. The protein domain TDBD (PFAM ID: PF16135) was detected in StSET genes of potato while it was absent in all other previously studied species. This study described three pollen-specific StSET genes in the potato genome. Expression analysis of four StSET genes under heat and drought in three potato clones revealed that these genes might have non-overlapping roles under different abiotic stress conditions and durations. The present study provides a comprehensive analysis of StSET genes in potatoes, and it serves as a basis for further functional characterisation of StSET genes towards understanding their underpinning biological mechanisms in conferring stress tolerance.

Exploring natural genetic variation in photosynthesis-related traits of barley in the field

Optimizing photosynthesis is considered an important strategy for improving crop yields to ensure food security. To evaluate the potential of using photosynthesis-related parameters in crop breeding programs, we measured chlorophyll fluorescence along with growth-related and morphological traits of 23 barley inbreds across different developmental stages in field conditions. The photosynthesis-related parameters were highly variable, changing with light intensity and developmental progression of plants. Yet, the variations in photosystem II (PSII) quantum yield observed among the inbreds in the field largely reflected the variations in CO2 assimilation properties in controlled climate chamber conditions, confirming that the chlorophyll fluorescence-based technique can provide proxy parameters of photosynthesis to explore genetic variations under field conditions. Heritability (H2) of the photosynthesis-related parameters in the field ranged from 0.16 for the quantum yield of non-photochemical quenching to 0.78 for the fraction of open PSII center. Two parameters, the maximum PSII efficiency in light-adapted state (H2 0.58) and the total non-photochemical quenching (H2 0.53), showed significant positive and negative correlations, respectively, with yield-related traits (dry weight per plant and net straw weight) in the barley inbreds. These results indicate the possibility of improving crop yield through optimizing photosynthetic light use efficiency by conventional breeding programs.

StCoExpNet: a global co-expression network analysis facilitates identifying genes underlying agronomic traits in potatoes

KEY MESSAGE

We constructed a gene expression atlas and co-expression network for potatoes and identified several novel genes associated with various agronomic traits. This resource will accelerate potato genetics and genomics research. Potato (Solanum tuberosum L.) is the world's most crucial non-cereal food crop and ranks third in food production after wheat and rice. Despite the availability of several potato transcriptome datasets at public databases like NCBI SRA, an effort has yet to be put into developing a global transcriptome atlas and a co-expression network for potatoes. The objectives of our study were to construct a global expression atlas for potatoes using publicly available transcriptome datasets, identify housekeeping and tissue-specific genes, construct a global co-expression network and identify co-expression clusters, investigate the transcriptional complexity of genes involved in various essential biological processes related to agronomic traits, and provide a web server (StCoExpNet) to easily access the newly constructed expression atlas and co-expression network to investigate the expression and co-expression of genes of interest. In this study, we used data from 2299 publicly available potato transcriptome samples obtained from 15 different tissues to construct a global transcriptome atlas. We found that roughly 87% of the annotated genes exhibited detectable expression in at least one sample. Among these, we identified 281 genes with consistent and stable expression levels, indicating their role as housekeeping genes. Conversely, 308 genes exhibited marked tissue-specific expression patterns. We exemplarily linked some co-expression clusters to important agronomic traits of potatoes, such as self-incompatibility, anthocyanin biosynthesis, tuberization, and defense responses against multiple pathogens. The dataset compiled here constitutes a new resource (StCoExpNet), which can be accessed at https://stcoexpnet.julius-kuehn.de . This transcriptome atlas and the co-expression network will accelerate potato genetics and genomics research.

Genetic mapping reveals new loci and alleles for flowering time and plant height using the double round-robin population of barley

Flowering time and plant height are two critical determinants of yield potential in barley (Hordeum vulgare). Despite their role in plant physiological regulation, a complete overview of the genetic complexity of flowering time and plant height regulation in barley is still lacking. Using a double round-robin population originated from the crossings of 23 diverse parental inbred lines, we aimed to determine the variance components in the regulation of flowering time and plant height in barley as well as to identify new genetic variants by single and multi-population QTL analyses and allele mining. Despite similar genotypic variance, we observed higher environmental variance components for plant height than flowering time. Furthermore, we detected new QTLs for flowering time and plant height. Finally, we identified a new functional allelic variant of the main regulatory gene Ppd-H1. Our results show that the genetic architecture of flowering time and plant height might be more complex than reported earlier and that a number of undetected, small effect, or low-frequency genetic variants underlie the control of these two traits.

Using drone-retrieved multispectral data for phenomic selection in potato breeding

Predictive breeding approaches, like phenomic or genomic selection, have the potential to increase the selection gain for potato breeding programs which are characterized by very large numbers of entries in early stages and the availability of very few tubers per entry in these stages. The objectives of this study were to (i) explore the capabilities of phenomic prediction based on drone-derived multispectral reflectance data in potato breeding by testing different prediction scenarios on a diverse panel of tetraploid potato material from all market segments and considering a broad range of traits, (ii) compare the performance of phenomic and genomic predictions, and (iii) assess the predictive power of mixed relationship matrices utilizing weighted SNP array and multispectral reflectance data. Predictive abilities of phenomic prediction scenarios varied greatly within a range of - 0.15 and 0.88 and were strongly dependent on the environment, predicted trait, and considered prediction scenario. We observed high predictive abilities with phenomic prediction for yield (0.45), maturity (0.88), foliage development (0.73), and emergence (0.73), while all other traits achieved higher predictive ability with genomic compared to phenomic prediction. When a mixed relationship matrix was used for prediction, higher predictive abilities were observed for 20 out of 22 traits, showcasing that phenomic and genomic data contained complementary information. We see the main application of phenomic selection in potato breeding programs to allow for the use of the principle of predictive breeding in the pot seedling or single hill stage where genotyping is not recommended due to high costs.

Transposable elements contribute to the establishment of the glycine shuttle in Brassicaceae species

C3 -C4 intermediate photosynthesis has evolved at least five times convergently in the Brassicaceae, despite this family lacking bona fide C4 species. The establishment of this carbon concentrating mechanism is known to require a complex suite of ultrastructural modifications, as well as changes in spatial expression patterns, which are both thought to be underpinned by a reconfiguration of existing gene-regulatory networks. However, to date, the mechanisms which underpin the reconfiguration of these gene networks are largely unknown. In this study, we used a pan-genomic association approach to identify genomic features that could confer differential gene expression towards the C3 -C4 intermediate state by analysing eight C3 species and seven C3 -C4 species from five independent origins in the Brassicaceae. We found a strong correlation between transposable element (TE) insertions in cis-regulatory regions and C3 -C4 intermediacy. Specifically, our study revealed 113 gene models in which the presence of a TE within a gene correlates with C3 -C4 intermediate photosynthesis. In this set, genes involved in the photorespiratory glycine shuttle are enriched, including the glycine decarboxylase P-protein whose expression domain undergoes a spatial shift during the transition to C3 -C4 photosynthesis. When further interrogating this gene, we discovered independent TE insertions in its upstream region which we conclude to be responsible for causing the spatial shift in GLDP1 gene expression. Our findings hint at a pivotal role of TEs in the evolution of C3 -C4 intermediacy, especially in mediating differential spatial gene expression.

Brassicaceae display variation in efficiency of photorespiratory carbon-recapturing mechanisms

Carbon-concentrating mechanisms enhance the carboxylase efficiency of Rubisco by providing supra-atmospheric concentrations of CO2 in its surroundings. Beside the C4 photosynthesis pathway, carbon concentration can also be achieved by the photorespiratory glycine shuttle which requires fewer and less complex modifications. Plants displaying CO2 compensation points between 10 ppm and 40 ppm are often considered to utilize such a photorespiratory shuttle and are termed 'C3-C4 intermediates'. In the present study, we perform a physiological, biochemical, and anatomical survey of a large number of Brassicaceae species to better understand the C3-C4 intermediate phenotype, including its basic components and its plasticity. Our phylogenetic analysis suggested that C3-C4 metabolism evolved up to five times independently in the Brassicaceae. The efficiency of the pathway showed considerable variation. Centripetal accumulation of organelles in the bundle sheath was consistently observed in all C3-C4-classified taxa, indicating a crucial role for anatomical features in CO2-concentrating pathways. Leaf metabolite patterns were strongly influenced by the individual species, but accumulation of photorespiratory shuttle metabolites glycine and serine was generally observed. Analysis of phosphoenolpyruvate carboxylase activities suggested that C4-like shuttles have not evolved in the investigated Brassicaceae. Convergent evolution of the photorespiratory shuttle indicates that it represents a distinct photosynthesis type that is beneficial in some environments.

A genomic panel for studying C3-C4 intermediate photosynthesis in the Brassiceae tribe

Research on C4 and C3-C4 photosynthesis has attracted significant attention because the understanding of the genetic underpinnings of these traits will support the introduction of its characteristics into commercially relevant crop species. We used a panel of 19 taxa of 18 Brassiceae species with different photosynthesis characteristics (C3 and C3-C4) with the following objectives: (i) create draft genome assemblies and annotations, (ii) quantify orthology levels using synteny maps between all pairs of taxa, (iii) ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠describe the phylogenetic relatedness across all the species, and (iv) track the evolution of C3-C4 intermediate photosynthesis in the Brassiceae tribe. Our results indicate that the draft de novo genome assemblies are of high quality and cover at least 90% of the gene space. Therewith we more than doubled the sampling depth of genomes of the Brassiceae tribe that comprises commercially important as well as biologically interesting species. The gene annotation generated high-quality gene models, and for most genes extensive upstream sequences are available for all taxa, yielding potential to explore variants in regulatory sequences. The genome-based phylogenetic tree of the Brassiceae contained two main clades and indicated that the C3-C4 intermediate photosynthesis has evolved five times independently. Furthermore, our study provides the first genomic support of the hypothesis that Diplotaxis muralis is a natural hybrid of D. tenuifolia and D. viminea. Altogether, the de novo genome assemblies and the annotations reported in this study are a valuable resource for research on the evolution of C3-C4 intermediate photosynthesis.

Affordable, accurate and unbiased RNA sequencing by manual library miniaturization: A case study in barley

We present an easy-to-reproduce manual miniaturized full-length RNA sequencing (RNAseq) library preparation workflow that does not require the upfront investment in expensive lab equipment or long setup times. With minimal adjustments to an established commercial protocol, we were able to manually miniaturize the RNAseq library preparation by a factor of up to 1:8. This led to cost savings for miniaturized library preparation of up to 86.1% compared to the gold standard. The resulting data were the basis of a rigorous quality control analysis that inspected: sequencing quality metrics, gene body coverage, raw read duplications, alignment statistics, read pair duplications, detected transcripts and sequence variants. We also included a deep dive data analysis identifying rRNA contamination and suggested ways to circumvent these. In the end, we could not find any indication of biases or inaccuracies caused by the RNAseq library miniaturization. The variance in detected transcripts was minimal and not influenced by the miniaturization level. Our results suggest that the workflow is highly reproducible and the sequence data suitable for downstream analyses such as differential gene expression analysis or variant calling.

Improving photosynthetic efficiency toward food security: Strategies, advances, and perspectives

Photosynthesis in crops and natural vegetation allows light energy to be converted into chemical energy and thus forms the foundation for almost all terrestrial trophic networks on Earth. The efficiency of photosynthetic energy conversion plays a crucial role in determining the portion of incident solar radiation that can be used to generate plant biomass throughout a growth season. Consequently, alongside the factors such as resource availability, crop management, crop selection, maintenance costs, and intrinsic yield potential, photosynthetic energy use efficiency significantly influences crop yield. Photosynthetic efficiency is relevant to sustainability and food security because it affects water use efficiency, nutrient use efficiency, and land use efficiency. This review focuses specifically on the potential for improvements in photosynthetic efficiency to drive a sustainable increase in crop yields. We discuss bypassing photorespiration, enhancing light use efficiency, harnessing natural variation in photosynthetic parameters for breeding purposes, and adopting new-to-nature approaches that show promise for achieving unprecedented gains in photosynthetic efficiency.

Convergently selected NPF2.12 coordinates root growth and nitrogen use efficiency in wheat and barley

Understanding the genetic and molecular function of nitrate sensing and acquisition across crop species will accelerate breeding of cultivars with improved nitrogen use efficiency (NUE). Here, we performed a genome-wide scan using wheat and barley accessions characterized under low and high N inputs that uncovered the NPF2.12 gene, encoding a homolog of the Arabidopsis nitrate transceptor NRT1.6 and other low-affinity nitrate transporters that belong to the MAJOR FACILITATOR SUPERFAMILY. Next, it is shown that variations in the NPF2.12 promoter correlated with altered NPF2.12 transcript levels where decreased gene expression was measured under low nitrate availability. Multiple field trials revealed a significantly enhanced N content in leaves and grains and NUE in the presence of the elite allele TaNPF2.12^TT grown under low N conditions. Furthermore, the nitrate reductase encoding gene NIA1 was up-regulated in npf2.12 mutant upon low nitrate concentrations, thereby resulting in elevated levels of nitric oxide (NO) production. This increase in NO correlated with the higher root growth, nitrate uptake, and N translocation observed in the mutant when compared to wild-type. The presented data indicate that the elite haplotype alleles of NPF2.12 are convergently selected in wheat and barley that by inactivation indirectly contribute to root growth and NUE by activating NO signaling under low nitrate conditions.

Optimal implementation of genomic selection in clone breeding programs-Exemplified in potato: I. Effect of selection strategy, implementation stage, and selection intensity on short-term genetic gain

Genomic selection (GS) is used in many animal and plant breeding programs to enhance genetic gain for complex traits. However, its optimal integration in clone breeding programs, for example potato, that up to now relied on phenotypic selection (PS) requires further research. In this study, we performed computer simulations based on an empirical genomic dataset of tetraploid potato to (i) investigate under a fixed budget how the weight of GS relative to PS, the stage of implementing GS, the correlation between an auxiliary trait and the target trait, the variance components, and the prediction accuracy affect the genetic gain of the target trait, (ii) determine the optimal allocation of resources maximizing the genetic gain of the target trait, and (iii) make recommendations to breeders how to implement GS in clone and especially potato breeding programs. In our simulation results, any selection strategy involving GS had a higher short-term genetic gain for the target trait than Standard-PS. In addition, we showed that implementing GS in consecutive selection stages can largely enhance short-term genetic gain and recommend the breeders to implement GS at single hills and A clone stages. Furthermore, we observed for selection strategies involving GS that the optimal allocation of resources maximizing the genetic gain of the target trait differed considerably from those typically used in potato breeding programs and, thus, require the adjustment of the selection and phenotyping intensities. The trends are described in our study. Therefore, our study provides new insight for breeders regarding how to optimally implement GS in a commercial potato breeding program to improve the short-term genetic gain for their target trait.

Benchmarking of structural variant detection in the tetraploid potato genome using linked-read sequencing

It has recently been shown that structural variants (SV) can have a higher impact on gene expression variation compared to single nucleotide variants (SNV) in different plant species. Additionally, SV were associated with phenotypic variation in several crops. However, compared to the established SV detection based on short-read sequencing, less approaches were described for linked-read based SV calling. We therefore evaluated the performance of six linked-read SV callers compared to an established short-read SV caller based on simulated linked-reads in tetraploid potato. The objectives of our study were to i) compare the performance of SV callers based on linked-read sequencing to short-read sequencing, ii) examine the influence of SV type, SV length, haplotype incidence (HI), as well as sequencing coverage on the SV calling performance in the tetraploid potato genome, and iii) evaluate the accuracy of detecting insertions by linked-read compared to short-read sequencing. We observed high break point resolutions (BPR) detecting short SV and slightly lower BPR for large SV. Our observations highlighted the importance of short-read signals provided by Manta and LinkedSV to detect short SV. Manta and NAIBR performed well for detecting larger deletions, inversions, and duplications. Detected large SV were weakly influenced by the HI. Furthermore, we illustrated that large insertions can be assembled by Novel-X. Our results suggest the usage of the short-read and linked-read SV callers Manta, NAIBR, LinkedSV, and Novel-X based on at least 90x linked-read sequencing coverage to ensure the detection of a broad range of SV in the tetraploid potato genome.

The double round-robin population unravels the genetic architecture of grain size in barley

Grain number, size and weight primarily determine the yield of barley. Although the genes regulating grain number are well studied in barley, the genetic loci and the causal gene for sink capacity are poorly understood. Therefore, the primary objective of our work was to dissect the genetic architecture of grain size and weight in barley. We used a multi-parent population developed from a genetic cross between 23 diverse barley inbreds in a double round-robin design. Seed size-related parameters such as grain length, grain width, grain area and thousand-grain weight were evaluated in the HvDRR population comprising 45 recombinant inbred line sub-populations. We found significant genotypic variation for all seed size characteristics, and observed 84% or higher heritability across four environments. The quantitative trait locus (QTL) detection results indicate that the genetic architecture of grain size is more complex than previously reported. In addition, both cultivars and landraces contributed positive alleles at grain size QTLs. Candidate genes identified using genome-wide variant calling data for all parental inbred lines indicated overlapping and potential novel regulators of grain size in cereals. Furthermore, our results indicated that sink capacity was the primary determinant of grain weight in barley.

Structural variants in the barley gene pool: precision and sensitivity to detect them using short-read sequencing and their association with gene expression and phenotypic variation

Structural variants (SV) of 23 barley inbreds, detected by the best combination of SV callers based on short-read sequencing, were associated with genome-wide and gene-specific gene expression and, thus, were evaluated to predict agronomic traits. In human genetics, several studies have shown that phenotypic variation is more likely to be caused by structural variants (SV) than by single nucleotide variants. However, accurate while cost-efficient discovery of SV in complex genomes remains challenging. The objectives of our study were to (i) facilitate SV discovery studies by benchmarking SV callers and their combinations with respect to their sensitivity and precision to detect SV in the barley genome, (ii) characterize the occurrence and distribution of SV clusters in the genomes of 23 barley inbreds that are the parents of a unique resource for mapping quantitative traits, the double round robin population, (iii) quantify the association of SV clusters with transcript abundance, and (iv) evaluate the use of SV clusters for the prediction of phenotypic traits. In our computer simulations based on a sequencing coverage of 25x, a sensitivity > 70% and precision > 95% was observed for all combinations of SV types and SV length categories if the best combination of SV callers was used. We observed a significant (P < 0.05) association of gene-associated SV clusters with global gene-specific gene expression. Furthermore, about 9% of all SV clusters that were within 5 kb of a gene were significantly (P < 0.05) associated with the gene expression of the corresponding gene. The prediction ability of SV clusters was higher compared to that of single-nucleotide polymorphisms from an array across the seven studied phenotypic traits. These findings suggest the usefulness of exploiting SV information when fine mapping and cloning the causal genes underlying quantitative traits as well as the high potential of using SV clusters for the prediction of phenotypes in diverse germplasm sets.

Accurate recombination estimation from pooled genotyping and sequencing: a case study on barley

Sexual reproduction involves meiotic recombination and the creation of crossing over between homologous chromosomes, which leads to new allele combinations. We present a new approach that uses the allele frequency differences and the physical distance of neighboring polymorphisms to estimate the recombination rate from pool genotyping or sequencing. This allows a considerable cost reduction compared to conventional mapping based on genotyping or sequencing data of single individuals. We evaluated the approach based on computer simulations at various genotyping depths and population sizes as well as applied it to experimental data of 45 barley populations, comprising 4182 RIL. High correlations between the recombination rates from this new pool genetic mapping approach and conventional mapping in simulated and experimental barley populations were observed. The proposed method therefore provides a reliable genetic map position and recombination rate estimation in defined genomic windows.

Combining QTL mapping and gene co-expression network analysis for prediction of candidate genes and molecular network related to yield in wheat

BACKGROUND

Wheat (Triticum aestivum L.) is an important cereal crop. Increasing grain yield for wheat is always a priority. Due to the complex genome of hexaploid wheat with 21 chromosomes, it is difficult to identify underlying genes by traditional genetic approach. The combination of genetics and omics analysis has displayed the powerful capability to identify candidate genes for major quantitative trait loci (QTLs), but such studies have rarely been carried out in wheat. In this study, candidate genes related to yield were predicted by a combined use of linkage mapping and weighted gene co-expression network analysis (WGCNA) in a recombinant inbred line population.

RESULTS

QTL mapping was performed for plant height (PH), spike length (SL) and seed traits. A total of 68 QTLs were identified for them, among which, 12 QTLs were stably identified across different environments. Using RNA sequencing, we scanned the 99,168 genes expression patterns of the whole spike for the recombinant inbred line population. By the combined use of QTL mapping and WGCNA, 29, 47, 20, 26, 54, 46 and 22 candidate genes were predicted for PH, SL, kernel length (KL), kernel width, thousand kernel weight, seed dormancy, and seed vigor, respectively. Candidate genes for different traits had distinct preferences. The known PH regulation genes Rht-B and Rht-D, and the known seed dormancy regulation genes TaMFT can be selected as candidate gene. Moreover, further experiment revealed that there was a SL regulatory QTL located in an interval of about 7 Mbp on chromosome 7A, named TaSL1, which also involved in the regulation of KL.

CONCLUSIONS

A combination of QTL mapping and WGCNA was applied to predicted wheat candidate genes for PH, SL and seed traits. This strategy will facilitate the identification of candidate genes for related QTLs in wheat. In addition, the QTL TaSL1 that had multi-effect regulation of KL and SL was identified, which can be used for wheat improvement. These results provided valuable molecular marker and gene information for fine mapping and cloning of the yield-related trait loci in the future.

Genomic prediction of the recombination rate variation in barley - A route to highly recombinogenic genotypes

Meiotic recombination is not only fundamental to the adaptation of sexually reproducing eukaryotes in nature but increased recombination rates facilitate the combination of favourable alleles into a single haplotype in breeding programmes. The main objectives of this study were to (i) assess the extent and distribution of the recombination rate variation in cultivated barley (Hordeum vulgare L.), (ii) quantify the importance of the general and specific recombination effects, and (iii) evaluate a genomic selection approach's ability to predict the recombination rate variation. Genetic maps were created for the 45 segregating populations that were derived from crosses among 23 spring barley inbreds with origins across the world. The genome-wide recombination rate among populations ranged from 0.31 to 0.73 cM/Mbp. The crossing design used in this study allowed to separate the general recombination effects (GRE) of individual parental inbreds from the specific recombination effects (SRE) caused by the combinations of parental inbreds. The variance of the genome-wide GRE was found to be about eight times the variance of the SRE. This finding indicated that parental inbreds differ in the efficiency of their recombination machinery. The ability to predict the chromosome or genome-wide recombination rate of an inbred ranged from 0.80 to 0.85. These results suggest that a reliable screening of large genetic materials for their potential to cause a high extent of genetic recombination in their progeny is possible, allowing to systematically manipulate the recombination rate using natural variation.

Improvement of prediction ability by integrating multi-omic datasets in barley

Background

Genomic prediction (GP) based on single nucleotide polymorphisms (SNP) has become a broadly used tool to increase the gain of selection in plant breeding. However, using predictors that are biologically closer to the phenotypes such as transcriptome and metabolome may increase the prediction ability in GP. The objectives of this study were to (i) assess the prediction ability for three yield-related phenotypic traits using different omic datasets as single predictors compared to a SNP array, where these omic datasets included different types of sequence variants (full-SV, deleterious-dSV, and tolerant-tSV), different types of transcriptome (expression presence/absence variation-ePAV, gene expression-GE, and transcript expression-TE) sampled from two tissues, leaf and seedling, and metabolites (M); (ii) investigate the improvement in prediction ability when combining multiple omic datasets information to predict phenotypic variation in barley breeding programs; (iii) explore the predictive performance when using SV, GE, and ePAV from simulated 3’end mRNA sequencing of different lengths as predictors.

Results

The prediction ability from genomic best linear unbiased prediction (GBLUP) for the three traits using dSV information was higher than when using tSV, all SV information, or the SNP array. Any predictors from the transcriptome (GE, TE, as well as ePAV) and metabolome provided higher prediction abilities compared to the SNP array and SV on average across the three traits. In addition, some (di)-similarity existed between different omic datasets, and therefore provided complementary biological perspectives to phenotypic variation. Optimal combining the information of dSV, TE, ePAV, as well as metabolites into GP models could improve the prediction ability over that of the single predictors alone.

Conclusions

The use of integrated omic datasets in GP model is highly recommended. Furthermore, we evaluated a cost-effective approach generating 3’end mRNA sequencing with transcriptome data extracted from seedling without losing prediction ability in comparison to the full-length mRNA sequencing, paving the path for the use of such prediction methods in commercial breeding programs.

Supplementary Information

The online version contains supplementary material available at (10.1186/s12864-022-08337-7).

Genetic Divergence of Lineage-Specific Tandemly Duplicated Gene Clusters in Four Diploid Potato Genotypes

Potato (Solanum tuberosum L.) is the most important non-grain food crop. Tandem duplication significantly contributes to genome evolution. The objectives of this study were to (i) identify tandemly duplicated genes and compare their genomic distributions across potato genotypes, (ii) investigate the bias in functional specificities, (iii) explore the relationships among coding sequence, promoter and expression divergences associated with tandemly duplicated genes, (iv) examine the role of tandem duplication in generating and expanding lineage-specific gene families, (v) investigate the evolutionary forces affecting tandemly duplicated genes, and (vi) assess the similarities and differences with respect to above mentioned aspects between cultivated genotypes and their wild-relative. In this study, we used well-annotated and chromosome-scale de novo genome assemblies of multiple potato genotypes. Our results showed that tandemly duplicated genes are abundant and dispersed through the genome. We found that several functional specificities, such as disease resistance, stress-tolerance, and biosynthetic pathways of tandemly duplicated genes were differentially enriched across multiple potato genomes. Our results indicated the existence of a significant correlation among expression, promoter, and protein divergences in tandemly duplicated genes. We found about one fourth of tandemly duplicated gene clusters as lineage-specific among multiple potato genomes, and these tended to localize toward centromeres and revealed distinct selection signatures and expression patterns. Furthermore, our results showed that a majority of duplicated genes were retained through sub-functionalization followed by genetic redundancy, while only a small fraction of duplicated genes was retained though neo-functionalization. The lineage-specific expansion of gene families by tandem duplication coupled with functional bias might have significantly contributed to potato's genotypic diversity, and, thus, to adaption to environmental stimuli.

Chromosome-scale reference genome assembly of a diploid potato clone derived from an elite variety

Potato (Solanum tuberosum L.) is one of the most important crops with a worldwide production of 370 million metric tons. The objectives of this study were (1) to create a high-quality consensus sequence across the two haplotypes of a diploid clone derived from a tetraploid elite variety and assess the sequence divergence from the available potato genome assemblies, as well as among the two haplotypes; (2) to evaluate the new assembly’s usefulness for various genomic methods; and (3) to assess the performance of phasing in diploid and tetraploid clones, using linked-read sequencing technology. We used PacBio long reads coupled with 10x Genomics reads and proximity ligation scaffolding to create the dAg1_v1.0 reference genome sequence. With a final assembly size of 812 Mb, where 750 Mb are anchored to 12 chromosomes, our assembly is larger than other available potato reference sequences and high proportions of properly paired reads were observed for clones unrelated by pedigree to dAg1. Comparisons of the new dAg1_v1.0 sequence to other potato genome sequences point out the high divergence between the different potato varieties and illustrate the potential of using dAg1_v1.0 sequence in breeding applications.

Mutation-Simulator: fine-grained simulation of random mutations in any genome

Summary

Mutation-Simulator allows the introduction of various types of sequence alterations in reference sequences, with reasonable compute-time even for large eukaryotic genomes. Its intuitive system for fine-grained control over mutation rates along the sequence enables the mimicking of natural mutation patterns. Using standard file formats for input and output data, it can easily be integrated into any development and benchmarking workflow for high-throughput sequencing applications.

Availability and implementation

Mutation-Simulator is written in Python 3 and the source code, documentation, help and use cases are available on the Github page at https://github.com/mkpython3/Mutation-Simulator. It is free for use under the GPL 3 license.

The maize shoot ionome: Its interaction partners, predictive power, and genetic determinants

An improved understanding of how to manipulate the accumulation and enrichment of mineral elements in aboveground plant tissues holds promise for future resource efficient and sustainable crop production. The objectives of this study were to (a) evaluate the influence of Fe regimes on mineral element concentrations and contents in the maize shoot as well as their correlations, (b) examine the predictive ability of physiological and morphological traits of individual genotypes of the IBM population from the concentration of mineral elements, and (c) identify genetic factors influencing the mineral element composition within and across Fe regimes. We evaluated the concentration and content of 12 mineral elements in shoots of the IBM population grown in sufficient and deficient Fe regimes and found for almost all mineral elements a significant (α = 0.05) genotypic variance. Across all mineral elements, the variance of genotype*Fe regime interactions was on average even more pronounced. High prediction abilities indicated that mineral elements are powerful predictors of morphological and physiological traits. Furthermore, our results suggest that ZmHMA2/3 and ZmMOT1 are major players in the natural genetic variation of Cd and Mo concentrations and contents of maize shoots, respectively.

Aroma and quality of breads baked from old and modern wheat varieties and their prediction from genomic and flour-based metabolite profiles

Bread aroma is the principal characteristic perceived by the consumer yet it is mostly disregarded in the product chain. The main aim of this study was to evaluate the potential to include bread aroma as a new target criterion into the wheat product chain. The objectives of our study were to (i) quantify the influence of genetic versus environmental factors on the bread aroma and quality characteristics, (ii) evaluate whether bread baked from modern wheat varieties differ in terms of aroma from those baked from old varieties, and (iii) compare genomic and metabolomic approaches for their efficiency to predict bread aroma and quality characteristics in a wheat breeding program. Agronomic characters as well as bread aroma and quality traits were assessed for 18 old and 22 modern winter wheat varieties evaluated at up to three locations in Germany. Metabolite profiles of all 120 flour samples were collected using a 7200 GC-QTOF. Considerable differences in the adjusted entry means for all examined bread aroma and quality characters were observed. For aroma, which was rated on a scale from 1 to 9, the adjusted entry means varied for the 40 wheat varieties between 3 and 8. In contrast, the aroma of bread prepared from old and modern wheat varieties did not differ significantly (P < 0.05). Bread aroma was not significantly (P < 0.05) correlated with grain yield, which suggested that it is possible to select for the former character in wheat breeding programs without reducing the gain of selection for the latter. Finally, we have shown that bread aroma can be better predicted using a combination of metabolite and SNP genotyping profiles instead of the SNP genotyping profile only. In conclusion, we have illustrated possibilities to increase the quality of wheat for consumers in the product chain.

Transcriptomic and presence/absence variation in the barley genome assessed from multi-tissue mRNA sequencing and their power to predict phenotypic traits

Background

Barley is the world’s fourth most cultivated cereal and is an important crop model for genetic studies. One layer of genomic information that remains poorly explored in barley is presence/absence variation (PAV), which has been suggested to contribute to phenotypic variation of agronomic importance in various crops.

Results

An mRNA sequencing approach was used to study genomic PAV and transcriptomic variation in 23 spring barley inbreds. 1502 new genes identified here were physically absent from the Morex reference sequence, and 11,523 previously unannotated genes were not expressed in Morex. The procedure applied to detect expression PAV revealed that more than 50% of all genes of our data set are not expressed in all inbreds. Interestingly, expression PAV were not in strong linkage disequilibrium with neighboring sequence variants (SV), and therefore provided an additional layer of genetic information. Optimal combinations of expression PAV, SV, and gene abundance data could enhance the prediction accuracy of predicting three different agronomic traits.

Conclusions

Our results highlight the advantage of mRNA sequencing for genomic prediction over other technologies, as it allows extracting multiple layers of genomic data from a single sequencing experiment. Finally, we propose low coverage mRNA sequencing based characterization of breeding material harvested as seedlings in petri dishes as a powerful and cost efficient approach to replace current single nucleotide polymorphism (SNP) based characterizations.

Iron Retention in Root Hemicelluloses Causes Genotypic Variability in the Tolerance to Iron Deficiency-Induced Chlorosis in Maize

Antagonistic interactions of phosphorus (P) hamper iron (Fe) acquisition by plants and can cause Fe deficiency-induced chlorosis. To determine the physiological processes underlying adverse Fe-P interactions, the maize lines B73 and Mo17, which differ in chlorosis susceptibility, were grown hydroponically at different Fe:P ratios. In the presence of P, Mo17 became more chlorotic than B73. The higher sensitivity of Mo17 to Fe deficiency was not related to Fe-P interactions in leaves but to lower Fe translocation to shoots, which coincided with a larger pool of Fe being fixed in the root apoplast of P-supplied Mo17 plants. Fractionating cell wall components from roots showed that most of the cell wall-contained P accumulated in pectin, whereas most of the Fe was bound to root hemicelluloses, revealing that co-precipitation of Fe and P in the apoplast was not responsible for Fe inactivation in roots. A negative correlation between chlorophyll index and hemicellulose-bound Fe in 85 inbred lines of the intermated maize B73 × Mo17 (IBM) population indicated that apoplastic Fe retention contributes to genotypic differences in chlorosis susceptibility of maize grown under low Fe supplies. Our study indicates that Fe retention in the hemicellulose fraction of roots is an important determinant in the tolerance to Fe deficiency-induced chlorosis of graminaceous plant species with low phytosiderophore release, like maize.

Prospects and Potential Uses of Genomic Prediction of Key Performance Traits in Tetraploid Potato

Genomic prediction is a routine tool in breeding programs of most major animal and plant species. However, its usefulness for potato breeding has not yet been evaluated in detail. The objectives of this study were to (i) examine the prospects of genomic prediction of key performance traits in a diversity panel of tetraploid potato modeling additive, dominance, and epistatic effects, (ii) investigate the effects of size and make up of training set, number of test environments and molecular markers on prediction accuracy, and (iii) assess the effect of including markers from candidate genes on the prediction accuracy. With genomic best linear unbiased prediction (GBLUP), BayesA, BayesCπ, and Bayesian LASSO, four different prediction methods were used for genomic prediction of relative area under disease progress curve after a Phytophthora infestans infection, plant maturity, maturity corrected resistance, tuber starch content, tuber starch yield (TSY), and tuber yield (TY) of 184 tetraploid potato clones or subsets thereof genotyped with the SolCAP 8.3k SNP array. The cross-validated prediction accuracies with GBLUP and the three Bayesian approaches for the six evaluated traits ranged from about 0.5 to about 0.8. For traits with a high expected genetic complexity, such as TSY and TY, we observed an 8% higher prediction accuracy using a model with additive and dominance effects compared with a model with additive effects only. Our results suggest that for oligogenic traits in general and when diagnostic markers are available in particular, the use of Bayesian methods for genomic prediction is highly recommended and that the diagnostic markers should be modeled as fixed effects. The evaluation of the relative performance of genomic prediction vs. phenotypic selection indicated that the former is superior, assuming cycle lengths and selection intensities that are possible to realize in commercial potato breeding programs.

A high-density SNP genotyping array for Brassica napus and its ancestral diploid species based on optimised selection of single-locus markers in the allotetraploid genome

The Brassica napus Illumina array provides genome-wide markers linked to the available genome sequence, a significant tool for genetic analyses of the allotetraploid B. napus and its progenitor diploid genomes. A high-density single nucleotide polymorphism (SNP) Illumina Infinium array, containing 52,157 markers, was developed for the allotetraploid Brassica napus. A stringent selection process employing the short probe sequence for each SNP assay was used to limit the majority of the selected markers to those represented a minimum number of times across the highly replicated genome. As a result approximately 60 % of the SNP assays display genome-specificity, resolving as three clearly separated clusters (AA, AB, and BB) when tested with a diverse range of B. napus material. This genome specificity was supported by the analysis of the diploid ancestors of B. napus, whereby 26,504 and 29,720 markers were scorable in B. oleracea and B. rapa, respectively. Forty-four percent of the assayed loci on the array were genetically mapped in a single doubled-haploid B. napus population allowing alignment of their physical and genetic coordinates. Although strong conservation of the two positions was shown, at least 3 % of the loci were genetically mapped to a homoeologous position compared to their presumed physical position in the respective genome, underlying the importance of genetic corroboration of locus identity. In addition, the alignments identified multiple rearrangements between the diploid and tetraploid Brassica genomes. Although mostly attributed to genome assembly errors, some are likely evidence of rearrangements that occurred since the hybridisation of the progenitor genomes in the B. napus nucleus. Based on estimates for linkage disequilibrium decay, the array is a valuable tool for genetic fine mapping and genome-wide association studies in B. napus and its progenitor genomes.

First steps to understand heat tolerance of temperate maize at adult stage: identification of QTL across multiple environments with connected segregating populations

Dents were more heat tolerant than Flints. QTL for heat tolerance with respect to grain yield at field conditions were identified considering multiple populations and environments. High temperatures have the potential to cause severe damages to maize production. This study aims to elucidate the genetic mechanisms of heat tolerance under field conditions in maize and the genome regions contributing to natural variation. In our study, heat tolerance was assessed on a multi-environment level under non-controlled field conditions for a set of connected intra- and interpool Dent and Flint populations. Our findings indicate that Dent are more heat tolerant during adult stage than Flint genotypes. We identified 11 quantitative trait loci (QTL) including 2 loci for heat tolerance with respect to grain yield. Furthermore, we identified six heat-tolerance and 112 heat-responsive candidate genes colocating with the previously mentioned QTL. To investigate their contribution to the response to heat stress and heat tolerance, differential expression and sequence variation of the identified candidate genes should be subjected to further research.

Comparison of statistical models for nested association mapping in rapeseed (Brassica napus L.) through computer simulations

BACKGROUND

Rapeseed (Brassica napus L.) is an important oilseed crop throughout the world, serving as source for edible oil and renewable energy. Development of nested association mapping (NAM) population and methods is of importance for quantitative trait locus (QTL) mapping in rapeseed. The objectives of the research were to compare the power of QTL detection 1- β(∗) (β(∗) is the empirical type II error rate) (i) of two mating designs, double haploid (DH-NAM) and backcross (BC-NAM), (ii) of different statistical models, and (iii) for different genetic situations.

RESULTS

The computer simulations were based on the empirical data of a single nucleotide polymorphism (SNP) set of 790 SNPs from 30 sequenced conserved genes of 51 accessions of world-wide diverse B. napus germplasm. The results showed that a joint composite interval mapping (JCIM) model had significantly higher power of QTL detection than a single marker model. The DH-NAM mating design showed a slightly higher power of QTL detection than the BC-NAM mating design. The JCIM model considering QTL effects nested within subpopulations showed higher power of QTL detection than the JCIM model considering QTL effects across subpopulations, when examing a scenario in which there were interaction effects by a few QTLs interacting with a few background markers as well as a scenario in which there were interaction effects by many QTLs (≥ 25) each with more than 10 background markers and the proportion of total variance explained by the interactions was higher than 75 %.

CONCLUSIONS

The results of our study support the optimal design as well as analysis of NAM populations, especially in rapeseed.

Agronomic and Seed Quality Traits Dissected by Genome-Wide Association Mapping in Brassica napus

In Brassica napus breeding, traits related to commercial success are of highest importance for plant breeders. However, such traits can only be assessed in an advanced developmental stage. Molecular markers genetically linked to such traits have the potential to accelerate the breeding process of B. napus by marker-assisted selection. Therefore, the objectives of this study were to identify (i) genome regions associated with the examined agronomic and seed quality traits, (ii) the interrelationship of population structure and the detected associations, and (iii) candidate genes for the revealed associations. The diversity set used in this study consisted of 405 B. napus inbred lines which were genotyped using a 6K single nucleotide polymorphism (SNP) array and phenotyped for agronomic and seed quality traits in field trials. In a genome-wide association study, we detected a total of 112 associations between SNPs and the seed quality traits as well as 46 SNP-trait associations for the agronomic traits with a P < 1.28e-05 (Bonferroni correction of α = 0.05) for the inbreds of the spring and winter trial. For the seed quality traits, a single SNP-sulfur concentration in seeds (SUL) association explained up to 67.3% of the phenotypic variance, whereas for the agronomic traits, a single SNP-blossom color (BLC) association explained up to 30.2% of the phenotypic variance. In a basic local alignment search tool (BLAST) search within a distance of 2.5 Mbp around these SNP-trait associations, 62 hits of potential candidate genes with a BLAST-score of ≥100 and a sequence identity of ≥70% to A. thaliana or B. rapa could be found for the agronomic SNP-trait associations and 187 hits of potential candidate genes for the seed quality SNP-trait associations.

Seedling development traits in Brassica napus examined by gene expression analysis and association mapping

BACKGROUND

An optimal seedling development of Brassica napus plants leads to a higher yield stability even under suboptimal growing conditions and has therefore a high importance for plant breeders. The objectives of our study were to (i) examine the expression levels of candidate genes in seedling leaves of B. napus and correlate these with seedling development as well as (ii) detect genome regions associated with gene expression levels and seedling development traits in B. napus by genome-wide association mapping.

RESULTS

The expression levels of the 15 candidate genes examined in the 509 B. napus inbreds showed an averaged standard deviation of 5.6 across all inbreds and ranged from 3.2 to 8.8. The gene expression differences between the 509 B. napus inbreds were more than adequate for the correlation with phenotypic variation of seedling development. The average of the absolute value correlations of the correlation coefficients of 0.11 were observed with a range from 0.00 to 0.39. The candidate genes GER1, AILP1, PECT, and FBP were strongly correlated with the seedling development traits. In a genome-wide association study, we detected a total of 63 associations between single nucleotide polymorphisms (SNPs) and the seedling development traits and 31 SNP-gene associations for the candidate genes with a P-value < 0.0001. For the projected leaf area traits we identified five different association hot spots on the chromosomes A2, A7, C3, C6, and C7.

CONCLUSION

A total of 99.4% of the adjacent SNPs on the A genome and 93.0% of the adjacent SNPs on the C genome had a distance smaller than the average range of linkage disequilibrium. Therefore, this genome-wide association study is expected to result on average in 14.7% of the possible power. Compared to previous studies in B. napus, the SNP marker density of our study is expected to provide a higher power to detect SNP-trait/-gene associations in the B. napus diversity set. The large number of associations detected for the examined 14 seedling development traits indicated that these are genetically complex inherited. The results of our analyses suggested that the studied genes ribulose 1,5-bisphosphate carboxylase/oxygenase small subunit (RBC) on the chromosomes A4 and C4 and fructose-1,6-bisphosphatase precursor (FBP) on the chromosomes A9 and C8 are cis-regulated.

Genome-wide expression profiling and phenotypic evaluation of European maize inbreds at seedling stage in response to heat stress

Background

Climate change will lead in the future to an occurrence of heat waves with a higher frequency and duration than observed today, which has the potential to cause severe damage to seedlings of temperate maize genotypes. In this study, we aimed to (I) assess phenotypic variation for heat tolerance of temperate European Flint and Dent maize inbred lines, (II) investigate the transcriptomic response of temperate maize to linearly increasing heat levels and, (III) identify genes associated with heat tolerance in a set of genotypes with contrasting heat tolerance behaviour.

Results

Strong phenotypic differences with respect to heat tolerance were observed between the examined maize inbred lines on a multi-trait level. We identified 607 heat responsive genes as well as 39 heat tolerance genes.

Conclusion

Our findings indicate that individual inbred lines developed different genetic mechanisms in response to heat stress. We applied a novel statistical approach enabling the integration of multiple genotypes and stress levels in the analysis of abiotic stress expression studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1282-1) contains supplementary material, which is available to authorized users.

Linkage mapping of Barley yellow dwarf virus resistance in connected populations of maize

BACKGROUND

With increasing winter temperatures, Barley yellow dwarf virus (BYDV) is expected to become an increasing problem in maize cultivation in Germany. Earlier studies revealed that BYDV has a negative impact on maize performance. Molecular markers would accelerate the development of BYDV resistant maize. Therefore, the objectives of this study were (i) the identification of quantitative trait loci (QTL) for BYDV resistance in five connected segregating maize populations in a field experiment and (ii) their comparison with the QTL detected under greenhouse conditions.

RESULTS

In linkage analyses of the traits virus extinction, infection rate, and the symptom red edges, a highly associated major QTL was identified on chromosome 10. This QTL explained 45% of the phenotypic variance for the traits virus extinction and infection rate and 30% for the symptom red edges.

CONCLUSION

We could show that BYDV resistance traits are oligogenically inherited. The QTL on chromosome 10 could be observed in the connected linkage analyses and in the single population analyses. Furthermore, this QTL could also be confirmed in the greenhouse experiment. Our results let suggest that this QTL is involved in multiple virus resistance and the markers are promising for marker assisted selection.

Genome-wide association mapping of iron homeostasis in the maize association population

Background

Iron (Fe) deficiency in plants is the result of low Fe soil availability affecting 30% of cultivated soils worldwide. To improve our understanding on Fe-efficiency this study aimed to (i) evaluate the influence of two different Fe regimes on morphological and physiological trait formation, (ii) identify polymorphisms statistically associated with morphological and physiological traits, and (iii) dissect the correlation between morphological and physiological traits using an association mapping population.

Results

The fine-mapping analyses on quantitative trait loci (QTL) confidence intervals of the intermated B73 × Mo17 (IBM) population provided a total of 13 and 2 single nucleotide polymorphisms (SNPs) under limited and adequate Fe regimes, respectively, which were significantly (FDR = 0.05) associated with cytochrome P450 94A1, invertase beta-fructofuranosidase insoluble isoenzyme 6, and a low-temperature-induced 65 kDa protein. The genome-wide association (GWA) analyses under limited and adequate Fe regimes provided in total 18 and 17 significant SNPs, respectively.

Conclusions

Significantly associated SNPs on a genome-wide level under both Fe regimes for the traits leaf necrosis (NEC), root weight (RW), shoot dry weight (SDW), water (H ₂O), and SPAD value of leaf 3 (SP3) were located in genes or recognition sites of transcriptional regulators, which indicates a direct impact on the phenotype. SNPs which were significantly associated on a genome-wide level under both Fe regimes with the traits NEC, RW, SDW, H ₂O, and SP3 might be attractive targets for marker assisted selection as well as interesting objects for future functional analyses.

Electronic supplementary material

The online version of this article (doi:10.1186/s12863-014-0153-0) contains supplementary material, which is available to authorized users.

Genes involved in barley yellow dwarf virus resistance of maize

The results of our study suggest that genes involved in general resistance mechanisms of plants contribute to variation of BYDV resistance in maize. With increasing winter temperatures in Europe, Barley yellow dwarf virus (BYDV) is expected to become a prominent problem in maize cultivation. Breeding for resistance is the best strategy to control the disease and break the transmission cycle of the virus. The objectives of our study were (1) to determine genetic variation with respect to BYDV resistance in a broad germplasm set and (2) to identify single nucleotide polymorphism (SNP) markers linked to genes that are involved in BYDV resistance. An association mapping population with 267 genotypes representing the world's maize gene pool was grown in the greenhouse. Plants were inoculated with BYDV-PAV using viruliferous Rhopalosiphum padi. In the association mapping population, we observed considerable genotypic variance for the trait virus extinction as measured by double antibody sandwich enzyme-linked immunosorbent assay (DAS-ELISA) and the infection rate. In a genome-wide association study, we observed three SNPs significantly [false discovery rate (FDR) = 0.05] associated with the virus extinction on chromosome 10 explaining together 25 % of the phenotypic variance and five SNPs for the infection rate on chromosomes 4 and 10 explaining together 33 % of the phenotypic variance. The SNPs significantly associated with BYDV resistance can be used in marker assisted selection and will accelerate the breeding process for the development of BYDV resistant maize genotypes. Furthermore, these SNPs were located within genes which were in other organisms described to play a role in general resistance mechanisms. This suggests that these genes contribute to variation of BYDV resistance in maize.

The genetic basis of natural variation for iron homeostasis in the maize IBM population

BACKGROUND

Iron (Fe) deficiency symptoms in maize (Zea mays subsp. mays) express as leaf chlorosis, growth retardation, as well as yield reduction and are typically observed when plants grow in calcareous soils at alkaline pH. To improve our understanding of genotypical variability in the tolerance to Fe deficiency-induced chlorosis, the objectives of this study were to (i) determine the natural genetic variation of traits related to Fe homeostasis in the maize intermated B73 × Mo17 (IBM) population, (ii) to identify quantitative trait loci (QTLs) for these traits, and (iii) to analyze expression levels of genes known to be involved in Fe homeostasis as well as of candidate genes obtained from the QTL analysis.

RESULTS

In hydroponically-grown maize, a total of 47 and 39 QTLs were detected for the traits recorded under limited and adequate supply of Fe, respectively.

CONCLUSIONS

From the QTL results, we were able to identify new putative candidate genes involved in Fe homeostasis under a deficient or adequate Fe nutritional status, like Ferredoxin class gene, putative ferredoxin PETF, metal tolerance protein MTP4, and MTP8. Furthermore, our expression analysis of candidate genes suggested the importance of trans-acting regulation for 2'-deoxymugineic acid synthase 1 (DMAS1), nicotianamine synthase (NAS3, NAS1), formate dehydrogenase 1 (FDH1), methylthioribose-1-phosphate isomerase (IDI2), aspartate/tyrosine/aromatic aminotransferase (IDI4), and methylthioribose kinase (MTK).

Species- and genome-wide dissection of the shoot ionome in Brassica napus and its relationship to seedling development

Knowing the genetic basis of the plant ionome is essential for understanding the control of nutrient transport and accumulation. The aim of this research was to (i) study mineral nutrient concentrations in a large and diverse set of Brassica napus, (ii) describe the relationships between the shoot ionome and seedling development, and (iii) identify genetic regions associated with variation of the shoot ionome. The plant material under study was a germplasm set consisting of 509 inbred lines that was genotyped by a 6K single nucleotide polymorphism (SNP) array and phenotyped by analyzing the concentrations of eleven mineral nutrients in the shoots of 30 days old seedlings. Among mineral concentrations, positive correlations were found, whereas mineral concentrations were mainly negatively correlated with seedling development traits from earlier studies. In a genome-wide association mapping approach, altogether 29 significantly associated loci were identified across seven traits after correcting for multiple testing. The associations included a locus with effects on the concentrations of Cu, Mn, and Zn on chromosome C3, and a genetic region with multiple associations for Na concentration on chromosome A9. This region was situated within an association hotspot close to SOS1, a key gene for Na tolerance in plants.

Ups and downs of a transcriptional landscape shape iron deficiency associated chlorosis of the maize inbreds B73 and Mo17

BACKGROUND

Improving nutrient homeostasis is a major challenge of a sustainable maize cultivation, and cornerstone to ensure food supply for a growing world population. Although, iron constitutes an important nutrient, iron availability is limited. In this respect, iron deficiency associated chlorosis causes severe yield losses every year. Natural variation of the latter trait has yet not been addressed in maize and was therefore studied in the present analysis.

RESULTS

In this study, we i) report about the contrasting chlorosis phenotypes of the inbreds B73 and Mo17 at 10 and 300 μM iron regime, ii) identified over 400 significantly regulated transcripts (FDR < 0.05) within both inbreds at these growth conditions by deep RNA-Sequencing, iii) linked the gained knowledge with QTL information about iron deficiency related traits within the maize intermated B73 by Mo17 (IBM) population, and iv) highlighted contributing molecular pathways. In this respect, several genes within methionine salvage pathway and phytosiderophore synthesis were found to present constitutively high expression in Mo17, even under sufficient iron supply. Moreover, the same expression pattern could be observed for two putative bHLH transcription factors. In addition, a number of differentially expressed genes showed a co-localisation with QTL confidence intervals for iron deficiency related traits within the IBM population.

CONCLUSIONS

Our study highlights differential iron deficiency associated chlorosis between B73 and Mo17 and represents a valuable resource for differentially expressed genes upon iron limitation and chlorosis response. Besides identifying two putative bHLH transcription factors, we propose that methionine salvage pathway and sterol metabolism amongst others; underlie the contrasting iron deficiency related chlorosis phenotype of both inbreds. Altogether, this study emphasizes a contribution of selected genes and pathways on natural trait variation within the IBM population.

Co-variation between seed dormancy, growth rate and flowering time changes with latitude in Arabidopsis thaliana

Life-history traits controlling the duration and timing of developmental phases in the life cycle jointly determine fitness. Therefore, life-history traits studied in isolation provide an incomplete view on the relevance of life-cycle variation for adaptation. In this study, we examine genetic variation in traits covering the major life history events of the annual species Arabidopsis thaliana: seed dormancy, vegetative growth rate and flowering time. In a sample of 112 genotypes collected throughout the European range of the species, both seed dormancy and flowering time follow a latitudinal gradient independent of the major population structure gradient. This finding confirms previous studies reporting the adaptive evolution of these two traits. Here, however, we further analyze patterns of co-variation among traits. We observe that co-variation between primary dormancy, vegetative growth rate and flowering time also follows a latitudinal cline. At higher latitudes, vegetative growth rate is positively correlated with primary dormancy and negatively with flowering time. In the South, this trend disappears. Patterns of trait co-variation change, presumably because major environmental gradients shift with latitude. This pattern appears unrelated to population structure, suggesting that changes in the coordinated evolution of major life history traits is adaptive. Our data suggest that A. thaliana provides a good model for the evolution of trade-offs and their genetic basis.

Tapping natural variation at functional level reveals allele specific molecular characteristics of potato invertase Pain-1

Biochemical, molecular and genetic studies emphasize the role of the potato vacuolar invertase Pain-1 in the accumulation of reducing sugars in potato tubers upon cold storage, and thereby its influence on the quality of potato chips and French fries. Previous studies showed that natural Pain-1 cDNA alleles were associated with better chip quality and higher tuber starch content. In this study, we focused on the functional characterization of these alleles. A genotype-dependent transient increase of total Pain-1 transcript levels in cold-stored tubers of six different genotypes as well as allele-specific expression patterns were detected. 3D modelling revealed putative structural differences between allelic Pain-1 proteins at the molecule's surface and at the substrate binding site. Furthermore, the yeast SUC2 mutant was complemented with Pain-1 cDNA alleles and enzymatic parameters of the heterologous expressed proteins were measured at 30 and 4 °C. Significant differences between the alleles were detected. The observed functional differences between Pain-1 alleles did not permit final conclusions on the mechanism of their association with tuber quality traits. Our results show that natural allelic variation at the functional level is present in potato, and that the heterozygous genetic background influences the manifestation of this variation.

Seedling development in a Brassica napus diversity set and its relationship to agronomic performance

Brassica napus L. is the leading European oilseed crop and has therefore a high economical importance. The objectives of our study were to examine (1) the patterns of phenotypic diversity in a species-wide B. napus germplasm set of 518 inbreds with respect to various seedling development, agronomic, and seed quality traits as well as (2) the interrelationship of the examined traits and their use in selection on correlated traits. The B. napus germplasm set was evaluated in greenhouse and field trials for several seedling development, agronomic, and seed quality traits. The traits were highly correlated within the individual trait categories and moderately correlated between the different trait categories. We observed differences in phenotypic diversity among the examined eight germplasm types. The reduction of phenotypic diversity was on average more pronounced for the seedling development traits than for the agronomic and seed quality traits, suggesting that plant breeders need to introgress new genetic variation with respect to the former.

High-throughput polymorphism detection and genotyping in Brassica napus using next-generation RAD sequencing

Background

The complex genome of rapeseed (Brassica napus) is not well understood despite the economic importance of the species. Good knowledge of sequence variation is needed for genetics approaches and breeding purposes. We used a diversity set of B. napus representing eight different germplasm types to sequence genome-wide distributed restriction-site associated DNA (RAD) fragments for polymorphism detection and genotyping.

Results

More than 113,000 RAD clusters with more than 20,000 single nucleotide polymorphisms (SNPs) and 125 insertions/deletions were detected and characterized. About one third of the RAD clusters and polymorphisms mapped to the Brassica rapa reference sequence. An even distribution of RAD clusters and polymorphisms was observed across the B. rapa chromosomes, which suggests that there might be an equal distribution over the Brassica oleracea chromosomes, too. The representation of Gene Ontology (GO) terms for unigenes with RAD clusters and polymorphisms revealed no signature of selection with respect to the distribution of polymorphisms within genes belonging to a specific GO category.

Conclusions

Considering the decreasing costs for next-generation sequencing, the results of our study suggest that RAD sequencing is not only a simple and cost-effective method for high-density polymorphism detection but also an alternative to SNP genotyping from transcriptome sequencing or SNP arrays, even for species with complex genomes such as B. napus.

Genome-wide association mapping of flowering time and northern corn leaf blight (Setosphaeria turcica) resistance in a vast commercial maize germplasm set

BACKGROUND

Setosphaeria turcica is a fungal pathogen that causes northern corn leaf blight (NCLB) which is a serious foliar disease in maize. In order to unravel the genetic architecture of the resistance against this disease, a vast association mapping panel comprising 1487 European maize inbred lines was used to (i) identify chromosomal regions affecting flowering time (FT) and northern corn leaf blight (NCLB) resistance, (ii) examine the epistatic interactions of the identified chromosomal regions with the genetic background on an individual molecular marker basis, and (iii) dissect the correlation between NCLB resistance and FT.

RESULTS

The single marker analyses performed for 8 244 single nucleotide polymorphism (SNP) markers revealed seven, four, and four SNP markers significantly (α=0.05, amplicon wise Bonferroni correction) associated with FT, NCLB, and NCLB resistance corrected for FT, respectively. These markers explained individually between 0.36 and 14.29% of the genetic variance of the corresponding trait.

CONCLUSIONS

The very well interpretable pattern of SNP associations observed for FT suggested that data from applied plant breeding programs can be used to dissect polygenic traits. This in turn indicates that the associations identified for NCLB resistance might be successfully used in marker-assisted selection programs. Furthermore, the associated genes are also of interest for further research concerning the mechanism of resistance to NCLB and plant diseases in general, because some of the associated genes have not been mentioned in this context so far.

Association analysis of photoperiodic flowering time genes in west and central African sorghum [Sorghum bicolor (L.) Moench]

BACKGROUND

Photoperiod-sensitive flowering is a key adaptive trait for sorghum (Sorghum bicolor) in West and Central Africa. In this study we performed an association analysis to investigate the effect of polymorphisms within the genes putatively related to variation in flowering time on photoperiod-sensitive flowering in sorghum. For this purpose a genetically characterized panel of 219 sorghum accessions from West and Central Africa was evaluated for their photoperiod response index (PRI) based on two sowing dates under field conditions.

RESULTS

Sorghum accessions used in our study were genotyped for single nucleotide polymorphisms (SNPs) in six genes putatively involved in the photoperiodic control of flowering time. Applying a mixed model approach and previously-determined population structure parameters to these candidate genes, we found significant associations between several SNPs with PRI for the genes CRYPTOCHROME 1 (CRY1-b1) and GIGANTEA (GI).

CONCLUSIONS

The negative values of Tajima's D, found for the genes of our study, suggested that purifying selection has acted on genes involved in photoperiodic control of flowering time in sorghum. The SNP markers of our study that showed significant associations with PRI can be used to create functional markers to serve as important tools for marker-assisted selection of photoperiod-sensitive cultivars in sorghum.

A candidate gene-based association study of tocopherol content and composition in rapeseed (Brassica napus)

Rapeseed (Brassica napus L.) is the most important oil crop of temperate climates. Rapeseed oil contains tocopherols, also known as vitamin E, which is an indispensable nutrient for humans and animals due to its antioxidant and radical scavenging abilities. Moreover, tocopherols are also important for the oxidative stability of vegetable oils. Therefore, seed oil with increased tocopherol content or altered tocopherol composition is a target for breeding. We investigated the role of nucleotide variations within candidate genes from the tocopherol biosynthesis pathway. Field trials were carried out with 229 accessions from a worldwide B. napus collection which was divided into two panels of 96 and 133 accessions. Seed tocopherol content and composition were measured by HPLC. High heritabilities were found for both traits, ranging from 0.62 to 0.94. We identified polymorphisms by sequencing selected regions of the tocopherol genes from the 96 accession panel. Subsequently, we determined the population structure (Q) and relative kinship (K) as detected by genotyping with genome-wide distributed SSR markers. Association studies were performed using two models, the structure-based GLM + Q and the PK-mixed model. Between 26 and 12 polymorphisms within two genes (BnaX.VTE3.a, BnaA.PDS1.c) were significantly associated with tocopherol traits. The SNPs explained up to 16.93% of the genetic variance for tocopherol composition and up to 10.48% for total tocopherol content. Based on the sequence information we designed CAPS markers for genotyping the 133 accessions from the second panel. Significant associations with various tocopherol traits confirmed the results from the first experiment. We demonstrate that the polymorphisms within the tocopherol genes clearly impact tocopherol content and composition in B. napus seeds. We suggest that these nucleotide variations may be used as selectable markers for breeding rapeseed with enhanced tocopherol quality.

Detection of epistatic interactions in association mapping populations: an example from tetraploid potato

Epistatic interactions among loci are expected to contribute substantially to variation of quantitative traits. The objectives of our research were to (i) compare a classical mixed-model approach with a combined mixed-model and analysis of variance approach for detecting epistatic interactions; (ii) examine using computer simulations the statistical power to detect additive-additive, additive-dominance and dominance-dominance epistatic interactions and (iii) detect epistatic interactions between candidate genes for resistance to leaf blight in a set of tetraploid potato clones. Our study was based on the genotypic and phenotypic data of 184 tetraploid potato cultivars as well as computer simulations. The number of significant (α* =1 × 10(-6)) epistatic interactions ranged for the three examined traits from 3 to 32. Our findings suggested that the combined mixed-model and analysis of variance approach leads in comparison with the classical mixed-model approach not to an increased rate of false-positives. The results of the computer simulations suggested that, if molecular markers are available that are in high LD (D'>0.9) with the trait-coding loci, the statistical power to detect epistatic interactions, which explain 5-10% of the phenotypic variance, was of a size that seems promising for their detection.

Patterns of molecular variation in a species-wide germplasm set of Brassica napus

Rapeseed (Brassica napus L.) is the leading European oilseed crop serving as source for edible oil and renewable energy. The objectives of our study were to (i) examine the population structure of a large and diverse set of B. napus inbred lines, (ii) investigate patterns of genetic diversity within and among different germplasm types, (iii) compare the two genomes of B. napus with regard to genetic diversity, and (iv) assess the extent of linkage disequilibrium (LD) between simple sequence repeat (SSR) markers. Our study was based on 509 B. napus inbred lines genotyped with 89 genome-specific SSR primer combinations. Both a principal coordinate analysis and software STRUCTURE revealed that winter types, spring types, and swedes were assigned to three major clusters. The genetic diversity of winter oilseed rape was lower than the diversity found in other germplasm types. Within winter oilseed rape types, a decay of genetic diversity with more recent release dates and reduced levels of erucic acid and glucosinolates was observed. The percentage of linked SSR loci pairs in significant (r (2) > Q (95 unlinked loci pairs)) LD was 6.29% for the entire germplasm set. Furthermore, LD decayed rapidly with distance, which will allow a relatively high mapping resolution in genome-wide association studies using our germplasm set, but, on the other hand, will require a high number of markers.