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.

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.

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.

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.

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.

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.

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.

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 TaNPF2.12TT 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.

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.

KEY MESSAGE: 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.

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.

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.

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.

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.

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.