@article{devasahayam2026nanopore,

title = {Nanopore sequencing reveals coordinated host and microbiome responses across barley genotypes},

author = {Bennet Rohan Fernando Devasahayam and Thomas McNeil and Tesfaye Wubet and Thomas Schmutzer},

doi = {10.1186/s12915-026-02688-3},

year  = {2026},

date = {2026-07-29},

urldate = {2026-07-29},

journal = {BMC Biology},

volume = {24},

number = {1},

pages = {177},

abstract = {BackgroundBarley (Hordeum vulgare L.) provides a suitable model for studying domestication-driven plant-microbiome interactions. Although wild, landrace, and modern genotypes host distinct rhizosphere communities, the extent to which roots and microbes reciprocally influence each other remains unclear. Here, we applied an integrated multi-omics approach combining long-read metagenomics, root transcriptomics, and plant genomics to understand genotype-specific host-microbiome coordination.ResultsOxford Nanopore whole metagenome sequencing (WMS) revealed genotype-associated shifts in rhizosphere communities across seasons. Functional profiling showed a conserved metabolic backbone including amino acid metabolism, energy production, and secondary metabolite biosynthesis, alongside genotype-dependent variation in carbohydrate metabolism and transport-associated pathways. Genome-resolved analysis through metagenome-assembled genomes (MAGs) further detailed the taxonomic and functional architecture of key rhizosphere lineages. Root transcriptome profiling identified extensive differential expression associated with microbial perception, signaling, defense, and metabolic processes. Integration of host and microbiome data revealed coordinated molecular patterns, indicating that barley genotypes are associated with distinct microbial assemblages and corresponding transcriptional responses.ConclusionsThese findings indicate that domestication has shaped coordinated associations between barley genotypes and their rhizosphere microbiomes, reflected in both microbial community composition and host transcriptional regulation. This work provides new insights into the evolutionary tuning of plant-microbiome relationships and highlights opportunities for microbiome-informed strategies in barley improvement.},

keywords = {DiP-DIAMANT, Host-microbiome interactions, Long-read nanopore sequencing, Metagenomics, Rhizosphere microbiome, Transcriptomics},

pubstate = {published},

tppubtype = {article}

}

@article{WOS:001673578400001,

title = {A novel approach to assessing the tracking accuracy of crop phenology  for multi-orbit and multi-feature Sentinel-1 time series},

author = {Johannes Low and Christopher Conrad and Steven Hill and Michael Thiel and Tobias Ullmann and Insa Otte},

doi = {10.1016/j.srs.2026.100370},

issn = {2666-0172},

year  = {2026},

date = {2026-06-01},

urldate = {2026-06-01},

journal = {SCIENCE OF REMOTE SENSING},

volume = {13},

keywords = {Canola, DEMMIN, DiP-ZAZIkI, InSAR coherence, Phenology, Sugar beet, Wheat},

pubstate = {published},

tppubtype = {article}

}

@article{vonmaydell2026population,

title = {Population structure, genetic diversity and core set construction of an international collection of 256 Melissa officinalis genotypes},

author = {Daniel Maydell and Johannes Schwerdt and Heike Lehnert and Yvonne P\"{o}schl-Grau and Thomas Schmutzer and Frank Marthe},

doi = {10.1186/s12870-026-08853-8},

issn = {1471-2229},

year  = {2026},

date = {2026-05-01},

urldate = {2026-05-01},

journal = {BMC Plant Biology},

volume = {26},

number = {1},

pages = {794},

abstract = {BackgroundMelissa officinalis (balm) is a perennial medicinal. Climate change and high cultivation costs necessitate the breeding of new cultivars with improved stress tolerance and high metabolite content. However, the high costs of phenotyping large collections limit breeding progress. This study characterized the genetic diversity and population structure of 256 genotypes from 215 international accessions using flow cytometry and genotyping by sequencing (GBS). The primary objective was to identify untapped genetic resources and establish core sets to streamline future breeding and research efforts.ResultsMorphological characterization and flow cytometry revealed a clear division by ploidy and subspecies. The collection comprised 209 diploid and three polyploid genotypes of ssp. officinalis (2C = 1.79 pg) and 44 tetraploid genotypes of ssp. altissima (4C = 3.57 pg). GBS generated 29,307 and 9,909 SNPs for the entire collection and a subset of ssp. officinalis genotypes, respectively. We identified significant genetic differentiation between the subspecies, as confirmed by PCA (PC1 = 69.9%), STRUCTURE, and hierarchical clustering. With 21,770 private alleles and HE = 0.38 subspecies altissima exhibited greater genetic divergence than ssp. officinalis (2,953 private alleles},

keywords = {DiP-DIAMANT, DiP-OptiLamia, Domestication, Gene flow, Gene pool, Genetic diversity, Identification (biology), Melissa officinalis, Officinalis, Population, Subspecies},

pubstate = {published},

tppubtype = {article}

}

@article{fierlej2026zmsweet,

title = {ZmSWEET Sucrose transporters expressed in the endosperm adjacent to the maize embryo are necessary for carbon partitioning and embryo growth [Preprint]},

author = {Yannick Fierlej and Laurine Grazer and Abdelsabour G. A. Khaled and Matthias Langer and \'{E}milie Montes and Thibaut Perez and Laura Gallo and Beno\^{i}t Lacombe and Philippe Nacry and H\'{e}l\`{e}ne Duplus-Bottin and Nicolas M. Doll and Ljudmilla Borisjuk and Hardy Rolletschek and Gwyneth Ingram and Peter M. Rogowsky and Thomas Widiez},

doi = {10.64898/2026.02.24.707659},

year  = {2026},

date = {2026-02-25},

urldate = {2026-02-25},

journal = {bioRxiv},

publisher = {Cold Spring Harbor Laboratory},

abstract = {Abstract In cereals such as maize, the kernel accumulates large quantities of storage compounds, including carbohydrates, lipids, and proteins, a process that requires tight regulation of nutrient transport. Seeds are composed of distinct tissues: the embryo, the endosperm, and maternal tissues that are symplastically isolated (not connected through plasmodesmata), necessitating specialized nutrient transfer mechanisms. In maize, nutrient transfer from maternal tissues to the endosperm via specialized basal endosperm transfer layer (BETL) cells is well characterized. However, nutrient transfer at the endosperm/embryo interface remains poorly understood. Consequently, the routes by which maternal carbon-derived sugars support embryo growth are still unclear. Our previous transcriptomic profiling uncovered a novel Endosperm domain Adjacent to the embryo Scutellum (EAS) with strong enrichment for transporter genes. Notably, genes encoding three sugar transporters from the SWEET (Sugars Will Eventually be Exported Transporters) family are highly and preferentially expressed in the EAS, suggesting the existence of a specialized sugar transfer mechanism at this interface. We show that the ZmSWEET proteins encoded by these genes are membrane-localized sucrose transporters and are functionally important for kernel development. A gene-edited triple zmsweet14a/14b/15a knock-out mutant exhibits reduced kernel weight and embryo size, significantly decreased embryo oil accumulation at maturity, and altered carbon partitioning within the kernel. In addition to these defects, mutant kernels display a significant reduction in primary root length during germination, indicating either lasting physiological consequences of disrupted sucrose transport during seed development or an additional role for these SWEET transporters during germination. Together, our findings demonstrate that sucrose transport at the endosperm/embryo interface is critical for proper carbon allocation, embryo development, and seed vigor, and identify the EAS as a key functional domain and potential target for improving seed composition.},

keywords = {DiP-Magdi, EAS, Embryo, Endosperm, Mutant, Scutellum, Sucrose, Transporter},

pubstate = {published},

tppubtype = {article}

}

@article{WOS:001681509300001,

title = {Fast barcode calling based on k-mer distances},

author = {Riko Corwin Uphoff and Steffen Schuler and Ivo Grosse and Matthias Muller-Hannemann},

doi = {10.1093/pnasnexus/pgag001},

year  = {2026},

date = {2026-02-01},

urldate = {2026-02-01},

journal = {PNAS NEXUS},

volume = {5},

number = {2},

keywords = {Algorithm engineering, DiP-Hyperspace, DNA barcode calling, Spatial transcriptomics},

pubstate = {published},

tppubtype = {article}

}

@article{WOS:001643722100001,

title = {Machine Learning-Driven Enzyme Mining: Opportunities, Challenges, and  Future Perspectives},

author = {Felix Moorhoff and Yanzi Zhang and Sizhe Qiu and Wenjuan Dong and David Medina-Ortiz and Jing Zhao and Mehdi D. Davari},

doi = {10.1021/acscatal.5c04814},

issn = {2155-5435},

year  = {2026},

date = {2026-01-01},

urldate = {2026-01-01},

journal = {ACS CATALYSIS},

volume = {16},

number = {1},

pages = {12-30},

keywords = {Biocatalysis, DiP-BioCasNavi, Enzyme discovery, Machine learning},

pubstate = {published},

tppubtype = {article}

}

@article{WOS:001631204600001,

title = {Whole-genome resequencing of the wild barley diversity collection: a  resource for identifying and exploiting genetic variation for cultivated  barley improvement},

author = {Rebecca Spanner and Ahmad H. Sallam and Yu Guo and Murukarthick Jayakodi and Axel Himmelbach and Anne Fiebig and Jamie Simmons and Gerit Bethke and Yoonjung Lee and Luis Willian Pacheco Arge and Yinjie Qiu and Ana Badea and Michael Baum and Francois Belzile and Roi Ben-David and Robert Brueggeman and Austin Case and Luigi Cattivelli and Michael Davis and Christoph Dockter and Jaroslav Dolezel and Antonin Dreiseitl and Ryan Gavin and Lior Glick and Stephan Greiner and Ruth Hamilton and Patrick M. Hayes and Scott Heisel and Cynthia Henson and Benjamin Kilian and Takao Komatsuda and Chengdao Li and Cheng Liu and Ramamurthy Mahalingam and Maren Maruschewski and Oadi Matny and Andreas Maurer and Klaus F. X. Mayer and Itay Mayrose and Matthew Moscou and Gary J. Muehlbauer and Youko Oono and Frank Ordon and Hakan Ozkan and Ales Pecinka and Dragan Perovic and Klaus Pillen and Mohammad Pourkheirandish and Joanne Russell and Jan Safar and Silvio Salvi and Miguel Sanchez-Garcia and Kazuhiro Sato and Thomas Schmutzer and Uwe Scholz and Jeness Scott and Gurcharn Singh Brar and Kevin P. Smith and Mark E. Sorrells and Manuel Spannagl and Nils Stein and Alessandro Tondelli and Roberto Tuberosa and James Tucker and Thomas Turkington and Jan Valkoun and Ramesh Pal Singh Verma and Marcus A. Vinje and Maria Korff and Jason G. Walling and Robbie Waugh and Roger P. Wise and Brande B. H. Wulff and Shengming Yang and Guoping Zhang and Peter L. Morrell and Martin Mascher and Brian J. Steffenson},

doi = {10.1093/g3journal/jkaf261},

issn = {2160-1836},

year  = {2026},

date = {2026-01-01},

urldate = {2026-01-01},

journal = {G3-GENES GENOMES GENETICS},

volume = {16},

number = {1},

abstract = {To exploit allelic variation in Hordeum vulgare subsp. spontaneum, the 

 Wild Barley Diversity Collection was subjected to paired-end Illumina 

 sequencing at similar to 9 x depth and evaluated for several agronomic 

 traits. We discovered 240.2 million single nucleotide polymorphisms 

 (SNPs) after alignment to the Morex V3 assembly and 24.4 million short 

 (1 to 50 bp) insertions and deletions. A genome-wide association study 

 of lemma color identified one marker-trait association (MTA) on 

 chromosome 1H close to HvBlp, the cloned gene controlling black lemma. 

 Four MTAs were identified for seedling stem rust resistance, including 2 

 novel loci on chromosomes 1H and 6H and one co-locating to the complex 

 RMRL1-RMRL2 locus on 5H. The whole-genome sequence data described herein 

 will facilitate the identification and utilization of new alleles for 

 barley improvement.},

keywords = {Genomic data, Sequencing, Variant analysis},

pubstate = {published},

tppubtype = {article}

}

@article{herrerarocha2026multitask,

title = {Multitask Bayesian Neural Networks for Multiparameter Protein Engineering [Preprint]},

author = {Fabio Herrera-Rocha and David Medina-Ortiz and Desiree Wyrzykala and Tharun Srinivasan Sudha and Mehdi D. Davari},

doi = {10.48550/arxiv.2608.18604},

year  = {2026},

date = {2026-01-01},

urldate = {2026-01-01},

journal = {arXiv},

publisher = {Cornell University},

abstract = {Simultaneously engineering multiple protein properties remains a major challenge. Existing machine learning-based pipelines for protein engineering often model properties separately, failing to capture their dependencies and trade-offs. Here, we systematically evaluate how Bayesian parameterization on Multitask Neural Networks can enable robust simultaneous protein engineering under scarce, noisy experimental data. We curated a comprehensive set of 27 multiparameter protein datasets. Then, we compared three algorithm architectures spanning low to full Bayesian parameterization across 16 sequence representations and dimensionality reduction (2,592 models). Bayesian Last Layer models delivered the strongest overall accuracy, generalization, and calibration, ranking as the top-performing model on 70% of benchmark datasets. Dimensionality reduction improved predictive performance by up to 42% and enhanced calibration up to 57% across architectures. Notably, simple One-Hot encoding achieved top performance on 25% of benchmark datasets, particularly with larger datasets. These results establish practical design principles for reliable and data-efficient multiparameter protein engineering.},

keywords = {Artificial neural network, Bayesian probability, Benchmark (surveying), Curse of dimensionality, Dimensionality reduction, DiP-BioCasNavi, DiP-LeFos, Feature engineering, Ranking (information retrieval), Set (abstract data type)},

pubstate = {published},

tppubtype = {article}

}

@article{fernandez2026silkroute,

title = {SilkRoute: A Descriptor-Driven Framework for Reproducible Multi-Source Biomolecular Data Acquisition [Preprint]},

author = {Diego Fern\'{a}ndez and Juli\'{a}n Alfonso Garc\'{i}a-Vinuesa and Diego \'{A}lvarez-Saravia and Michelle Soto-Garc\'{i}a and Jos\'{e} L. Medina-Franco and Julieta Sep\'{u}lveda-Y\'{a}\~{n}ez and Xavier F. Cadet and Fr\'{e}d\'{e}ric Cadet and Mehdi D. Davari and Roberto Uribe-Paredes and Fabio Herrera-Rocha and David Medina-Ortiz},

doi = {10.64898/2026.08.11.744100},

year  = {2026},

date = {2026-01-01},

urldate = {2026-01-01},

journal = {bioRxiv},

publisher = {Cold Spring Harbor Laboratory},

abstract = {Abstract Background Biomolecular dataset construction often requires coordinated retrieval from heterogeneous repositories, identifier mapping, cross-reference enrichment, source-specific parsing, and provenance recording. These operations are frequently implemented through project-specific scripts, making acquisition procedures difficult to inspect, reproduce, or adapt across studies. We present SilkRoute, an open-source Python framework that formalizes biomolecular data acquisition as descriptor-defined, source-aware, and provenance-tracked workflows, providing a reproducible foundation for multi-source biomolecular dataset construction. Results SilkRoute uses machine-readable YAML descriptors to specify dataset intent, biomolecular modality, workflow mode, query logic, enrichment resources, execution parameters, and export settings. These descriptors drive a common execution model that coordinates primary retrieval and downstream enrichment while preserving source-specific outputs, interaction evidence when available, the original workflow configuration, metadata, and run summaries. We evaluated this model through three representative acquisition scenarios spanning proteins, compounds, and molecular interactions. In the protein-centered workflow, SilkRoute retrieved 2,444 reviewed antimicrobial protein records from UniProt and generated complementary outputs from AlphaFold DB, InterPro, Pathway Commons, and the Protein Data Bank. In the compound-centered workflow, a ChEMBL IC 50 query produced 1,445,939 activity records organized into query-defined potency ranges. In the interaction-centered workflow, 2,253 UniProt protein records were expanded with 902,713 BioGRID interaction records and 5,702 STRING interaction-partner records. Across these scenarios, the framework successfully applied the same descriptor-defined acquisition model to distinct biomolecular entity types, retrieval strategies, enrichment paths, and output structures. Conclusions SilkRoute extends beyond sequence retrieval by providing a reusable acquisition layer for constructing multi-source biomolecular datasets. By separating primary retrieval from enrichment and preserving source-aware outputs together with workflow descriptors and execution metadata, the framework makes acquisition procedures easier to inspect, reproduce, archive, and adapt. SilkRoute does not replace biological curation, label validation, deduplication, partitioning, or benchmarking, but provides structured and traceable acquisition packages that support these downstream processes.},

keywords = {chEMBL, Data acquisition, Data integration, Data retrieval, DiP-BioCasNavi, DiP-LeFos, Identifier, Interoperability, Python (programming language), UniProt, Workflow},

pubstate = {published},

tppubtype = {article}

}

@article{WOS:001616552400001,

title = {Best Practices for Machine Learning-Assisted Protein Engineering},

author = {Fabio Herrera-Rocha and David Medina-Ortiz and Fabian Mauz and Juergen Pleiss and Mehdi D. Davari},

doi = {10.1021/acs.jcim.5c01983},

issn = {1549-9596},

year  = {2025},

date = {2025-12-01},

urldate = {2025-12-01},

journal = {JOURNAL OF CHEMICAL INFORMATION AND MODELING},

volume = {65},

number = {23},

pages = {12655-12667},

keywords = {DiP-LeFos, Machine learning, Optimization, Protein engineering},

pubstate = {published},

tppubtype = {article}

}

@article{WOS:001622101600001,

title = {Lipid MRI in plant science: principles and potential areas of  application},

author = {Ljudmilla Borisjuk and Thomas Neuberger and Hardy Rolletschek},

doi = {10.1093/jxb/eraf479},

issn = {0022-0957},

year  = {2025},

date = {2025-11-01},

urldate = {2025-11-01},

journal = {JOURNAL OF EXPERIMENTAL BOTANY},

keywords = {Artificial intelligence, DiP-Magdi, Lipid imaging, Magnetic resonance imaging, NMR spectroscopy, Phenotyping},

pubstate = {published},

tppubtype = {article}

}

@article{WOS:001593332300001,

title = {Tillering plasticity of drought-stressed barley genotypes under  different re-watering regimes},

author = {Sahel Soleimani and Philip Wichmann and Klaus Pillen and Kerstin Neumann and Andreas Maurer},

doi = {10.1186/s12870-025-07504-8},

issn = {1471-2229},

year  = {2025},

date = {2025-10-01},

urldate = {2025-10-01},

journal = {BMC PLANT BIOLOGY},

volume = {25},

number = {1},

abstract = {Background One future challenge of agriculture will be maintaining food 

 security in times of climate change. Future plant breeding, therefore, 

 has to account for the genotypes\' survival during drought and a good 

 recovery ability after rainfall events. We aimed at investigating the 

 re-tillering behavior of selected barley genotypes (cultivars and wild 

 barley introgression lines) in different drought and re-watering 

 scenarios, which were applied in a high-throughput phenotyping facility. 

 Re-tillering describes the activation of additional tillers after 

 post-stress irrigation. Results Twenty-three selected genotypes of the 

 barley NAM population HEB-25, along with three control genotypes, were 

 evaluated in four replicates under five distinct treatment conditions. 

 In this experiment, re-tillering was particularly pronounced in an 

 alternating watering and stress treatment, where the resumption of 

 irrigation post-stress enabled full recovery of the plants. However, it 

 was noted that while re-watering after a stress period promotes tiller 

 activation and the development of fertile ears, it also tends to 

 increase the number of sterile ears. The degree of sterile ear formation 

 varied significantly among different genotypes, highlighting the 

 critical role of genetic factors in modulating plant responses to 

 re-tillering and post-stress irrigation. It is important to note that 

 excessive re-tillering has been shown to exhibit a negative correlation 

 with fertile ear weight. Conclusions The impact of focusing on tiller 

 number and re-tillering behavior in future barley breeding may be 

 significant, particularly in the context of climate change. By selecting 

 for genotypes with appropriate tillering plasticity, breeders can 

 develop barley varieties that are more resilient to stress conditions 

 such as drought.},

keywords = {Drought tolerance, Genotype, Plant Breeding, Quantitative trait},

pubstate = {published},

tppubtype = {article}

}

@article{WOS:001574260900001,

title = {UPLC-ESI-TOF-MS Profiling of Metabolome Alterations in Barley  (Hordeum vulgare L.) Leaves Induced by Bipolaris  sorokiniana},

author = {Lisa Kurzweil and Timo D. Stark and Karina Hille and Felix Hoheneder and Jana Mrtva and Johann Hausladen and Miriam Lenk and Mohammed Saddik Motawia and Nicole Strittmatter and A. Corina Vlot and Klaus Pillen and Mette Sorensen and Birger L. Moller and Ralph Hueckelhoven and Corinna Dawid},

doi = {10.1021/acs.jafc.5c05419},

issn = {0021-8561},

year  = {2025},

date = {2025-10-01},

urldate = {2025-10-01},

journal = {JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY},

volume = {73},

number = {39},

pages = {24662-24687},

abstract = {Spot blotch of barley (Hordeum vulgare L.), caused by Bipolaris 

 sorokiniana, is responsible for major losses in crop yield. 

 Breeding-resistant barley varieties have proven to be an effective 

 countermeasure for protecting agricultural production. Plants react to 

 pathogen attacks by up-regulating secondary metabolites. Marker 

 compounds for a B. sorokiniana infection are examined by untargeted 

 UPLC-TOF-MS metabolomics and lipidomics techniques. Through the analysis 

 of nine quantitatively resistant and susceptible barley genotypes, 

 derived from the nested association mapping population HEB-25, followed 

 by structure identification experiments and spore germination assays, 57 

 metabolites are identified. In addition to previously known metabolites, 

 the unknown compounds 5-carboxydidehydroblumenol C-9-O-ss-d-glucoside 

 (46) and grasshopper ketone 3-sulfate (47) were elucidated. 

 5-Carboxyblumenol C-9-O-ss-d-glucoside (45) was described for the first 

 time in barley leaves. Pheophytin derivatives, oxylipins, 

 linolenate-conjugated lipids, and flavone glycosides were described for 

 the first time in connection with infections by phytopathogenic fungi or 

 resistance in barley.},

keywords = {Lipids, Metabolomics, MS imaging, Plant stress},

pubstate = {published},

tppubtype = {article}

}

@article{niels2025harnessing,

title = {Harnessing historical genebank data to accelerate pea breeding},

author = {Lanique Niels and Jochen Christoph Reif and Lars-Gernot Otto and Vilson Mirdita and Markus Oppermann and Ulrike Lohwasser and Matthias Kotter and Stephan Weise and Samira El Hanafi},

doi = {10.1007/s00122-025-05032-5},

issn = {0040-5752, 1432-2242},

year  = {2025},

date = {2025-09-09},

urldate = {2025-09-09},

journal = {Theoretical and Applied Genetics},

volume = {138},

number = {10},

pages = {243},

abstract = {The German Federal Ex Situ Genebank for Agricultural and Horticultural Crops (IPK) harbours over 3000 pea plant genetic resources (PGRs), backed up by corresponding information across 16 key agronomic and economical traits. The unbalanced structure and inconsistent format of this historical data has precluded effective leverage of genebank accessions, despite the opportunities contained in its genetic diversity. Therefore, a three-step statistical approach founded in linear mixed models was implemented to enable a rigorous and targeted data curation. Spring accessions revealed considerable breeding potential, with protein content exceeding market standards by almost one-fifth and with hundred grain weight that could match the upper limits reported for European elite varieties. This variation is embedded within structured populations, comprising five convarieties including sugar snaps and field pea, adding value for breeding across diverse morphotypes and market segments. Winter accessions demonstrated cold resilience, with post-winter survival rate up to 79.27% under minimum temperatures as low as − 17.1 °C. This variation is of particular relevance given the limited availability of winter-hardy cultivars able to evade summer drought and heat stresses. Transformation of the IPK Genebank into a bio-digital resource redirects formerly static material into central leverage for plant breeding in view of contemporary challenges. As such, this investigation activated the IPK pea population for use in among others breeding for a wide variety of ideotypes, research into adaptation, and future combination with omics studies.},

keywords = {Agriculture, Breeding program, Cultivar, DiP-DiPisum, Germplasm, Leverage (statistics), Plant Breeding, Population},

pubstate = {published},

tppubtype = {article}

}

@article{WOS:001565394900001,

title = {Integrating the landscape scale supports SAR-based detection and  assessment of the phenological development at the field level},

author = {Johannes Low and Steven Hill and Insa Otte and Christoph Friedrich and Michael Thiel and Tobias Ullmann and Christopher Conrad},

doi = {10.3389/frsen.2025.1610005},

year  = {2025},

date = {2025-08-01},

urldate = {2025-08-01},

journal = {FRONTIERS IN REMOTE SENSING},

volume = {6},

keywords = {DEMMIN, DiP-ZAZIkI, InSAR coherence, Phenology, Sentinel-1},

pubstate = {published},

tppubtype = {article}

}

@article{WOS:001513545300001,

title = {New loci and candidate genes in spring two-rowed barley detected through  meta-analysis of a field trial European network},

author = {Francesc Montardit-Tarda and Ana M. Casas and William T. B. Thomas and Florian Schnaithmann and Rajiv Sharma and Salar Shaaf and Chiara Campoli and Joanne Russell and Luke Ramsay and Micha M. Bayer and Stefano Delbono and Marko Jaaskelainen and Maitry Paul and Frederick L. Stoddard and Andrea Visioni and Andrew J. Flavell and Klaus Pillen and Benjamin Kilian and Andreas Graner and Laura Rossini and Robbie Waugh and Luigi Cattivelli and Alan H. Schulman and Alessandro Tondelli and Ernesto Igartua},

doi = {10.1007/s00122-025-04934-8},

issn = {0040-5752},

year  = {2025},

date = {2025-07-01},

urldate = {2025-07-01},

journal = {THEORETICAL AND APPLIED GENETICS},

volume = {138},

number = {7},

abstract = {Key messageA dense genome-wide meta-analysis provides new QTLs, reveals 

 breeding history trends and identifies new candidate genes for yield, 

 plant height, grain weight, and heading time of spring 

 barley.AbstractThis study contributes new knowledge on quantitative 

 trait loci (QTLs) and candidate genes for adaptive traits and yield in 

 two-rowed spring barley. A meta-analysis of a network of field trials, 

 varying in latitude and sowing date, with 151 cultivars across several 

 European countries, increased QTL detection power compared to 

 single-trial analyses. The traits analysed were heading date (HD), plant 

 height (PH), thousand-grain weight (TGW), and grain yield (GY). Breaking 

 down the analysis by the main genotype-by-environment trends revealed 

 QTLs and candidate genes specific to conditions like sowing date and 

 latitude. A historical look on the evolution of QTL frequencies revealed 

 that early selection focused on PH and TGW, likely due to their high 

 heritability. GY selection occurred later, facilitated by reduced 

 variance in other traits. The study observed that favourable alleles for 

 plant height were often fixed before those for grain yield and TGW. Some 

 regions showed linkage in repulsion, suggesting targets for future 

 breeding. Several candidate genes were identified, including known genes 

 and new candidates based on orthology with rice. Remarkably, the 

 deficiens allele of gene Vrs1 appears associated with higher GY. These 

 findings provide valuable insights for barley breeders aiming to improve 

 yield and other agronomic traits.},

keywords = {Agricultural Genetics, Drought tolerance, Genotype, Plant Breeding, Quantitative trait},

pubstate = {published},

tppubtype = {article}

}

@article{WOS:001430386400001,

title = {Profiling and Bioactivity of Polyphenols from the Omani Medicinal Plant  Terminalia dhofarica (syn. Anogeissus dhofarica)},

author = {Jonas Kappen and Luay Rashan and Katrin Franke and Ludger A. Wessjohann},

doi = {10.3390/molecules30040952},

year  = {2025},

date = {2025-02-01},

urldate = {2025-02-01},

journal = {MOLECULES},

volume = {30},

number = {4},

keywords = {Antibiotic, DiP-Hyperspace, NMR spectroscopy, Phytochemical profiling, Structure elucidation, UHPLC-HRMS},

pubstate = {published},

tppubtype = {article}

}

@article{WOS:001411678300001,

title = {A barley pan-transcriptome reveals layers of genotype-dependent  transcriptional complexity},

author = {Wenbin Guo and Miriam Schreiber and Vanda B. Marosi and Paolo Bagnaresi and Morten Egevang Jorgensen and Katarzyna B. Braune and Ken Chalmers and Brett Chapman and Viet Dang and Christoph Dockter and Anne Fiebig and Geoffrey B. Fincher and Agostino Fricano and John Fuller and Allison Haaning and Georg Haberer and Axel Himmelbach and Murukarthick Jayakodi and Yong Jia and Nadia Kamal and Peter Langridge and Chengdao Li and Qiongxian Lu and Thomas Lux and Martin Mascher and Klaus F. X. Mayer and Nicola Mccallum and Linda Milne and Gary J. Muehlbauer and Martin T. S. Nielsen and Sudharsan Padmarasu and Pai Rosager Pedas and Klaus Pillen and Curtis Pozniak and Magnus W. Rasmussen and Kazuhiro Sato and Thomas Schmutzer and Uwe Scholz and Danuta Schueler and Hana Simkova and Birgitte Skadhauge and Nils Stein and Nina W. Thomsen and Cynthia Voss and Penghao Wang and Ronja Wonneberger and Xiao-Qi Zhang and Guoping Zhang and Luigi Cattivelli and Manuel Spannagl and Micha Bayer and Craig Simpson and Runxuan Zhang and Robbie Waugh},

doi = {10.1038/s41588-024-02069-y},

issn = {1061-4036},

year  = {2025},

date = {2025-02-01},

urldate = {2025-02-01},

journal = {NATURE GENETICS},

volume = {57},

number = {2},

abstract = {A pan-transcriptome describes the transcriptional and 

 post-transcriptional consequences of genome diversity from multiple 

 individuals within a species. We developed a barley pan-transcriptome 

 using 20 inbred genotypes representing domesticated barley diversity by 

 generating and analyzing short- and long-read RNA-sequencing datasets 

 from multiple tissues. To overcome single reference bias in transcript 

 quantification, we constructed genotype-specific reference transcript 

 datasets (RTDs) and integrated these into a linear pan-genome framework 

 to create a pan-RTD, allowing transcript categorization as core, shell 

 or cloud. Focusing on the core (expressed in all genotypes), we observed 

 significant transcript abundance variation among tissues and between 

 genotypes driven partly by RNA processing, gene copy number, structural 

 rearrangements and conservation of promotor motifs. Network analyses 

 revealed conserved co-expression module::tissue correlations and 

 frequent functional diversification. To complement the 

 pan-transcriptome, we constructed a comprehensive cultivar (cv.) Morex 

 gene-expression atlas and illustrate how these combined datasets can be 

 used to guide biological inquiry.},

keywords = {Gene expression, Pan-genome, Pan-transcriptome, Plant genetics, RNA sequencing},

pubstate = {published},

tppubtype = {article}

}

@article{WOS:001353822800001,

title = {Structural variation in the pangenome of wild and domesticated barley},

author = {Murukarthick Jayakodi and Qiongxian Lu and Helene Pidon and M. Timothy Rabanus-Wallace and Micha Bayer and Thomas Lux and Yu Guo and Benjamin Jaegle and Ana Badea and Wubishet Bekele and Gurcharn S. Brar and Katarzyna Braune and Boyke Bunk and Kenneth J. Chalmers and Brett Chapman and Morten Egevang Jorgensen and Jia-Wu Feng and Manuel Feser and Anne Fiebig and Heidrun Gundlach and Wenbin Guo and Georg Haberer and Mats Hansson and Axel Himmelbach and Iris Hoffie and Robert E. Hoffie and Haifei Hu and Sachiko Isobe and Patrick Koenig and Sandip M. Kale and Nadia Kamal and Gabriel Keeble-Gagnere and Beat Keller and Manuela Knauft and Ravi Koppolu and Simon G. Krattinger and Jochen Kumlehn and Peter Langridge and Chengdao Li and Marina P. Marone and Andreas Maurer and Klaus F. X. Mayer and Michael Melzer and Gary J. Muehlbauer and Emiko Murozuka and Sudharsan Padmarasu and Dragan Perovic and Klaus Pillen and Pierre A. Pin and Curtis J. Pozniak and Luke Ramsay and Pai Rosager Pedas and Twan Rutten and Shun Sakuma and Kazuhiro Sato and Danuta Schueler and Thomas Schmutzer and Uwe Scholz and Miriam Schreiber and Kenta Shirasawa and Craig Simpson and Birgitte Skadhauge and Manuel Spannagl and Brian J. Steffenson and Hanne C. Thomsen and Josquin F. Tibbits and Martin Toft Simmelsgaard Nielsen and Corinna Trautewig and Dominique Vequaud and Cynthia Voss and Penghao Wang and Robbie Waugh and Sharon Westcott and Magnus Wohlfahrt Rasmussen and Runxuan Zhang and Xiao-Qi Zhang and Thomas Wicker and Christoph Dockter and Martin Mascher and Nils Stein},

doi = {10.1038/s41586-024-08187-1},

issn = {0028-0836},

year  = {2024},

date = {2024-12-01},

urldate = {2024-12-01},

journal = {NATURE},

volume = {636},

number = {8043},

abstract = {Pangenomes are collections of annotated genome sequences of multiple 

 individuals of a species1. The structural variants uncovered by these 

 datasets are a major asset to genetic analysis in crop plants2. Here we 

 report a pangenome of barley comprising long-read sequence assemblies of 

 76 wild and domesticated genomes and short-read sequence data of 1,315 

 genotypes. An expanded catalogue of sequence variation in the crop 

 includes structurally complex loci that are rich in gene copy number 

 variation. To demonstrate the utility of the pangenome, we focus on four 

 loci involved in disease resistance, plant architecture, nutrient 

 release and trichome development. Novel allelic variation at a powdery 

 mildew resistance locus and population-specific copy number gains in a 

 regulator of vegetative branching were found. Expansion of a family of 

 starch-cleaving enzymes in elite malting barleys was linked to shifts in 

 enzymatic activity in micro-malting trials. Deletion of an enhancer 

 motif is likely to change the developmental trajectory of the hairy 

 appendages on barley grains. Our findings indicate that allelic 

 diversity at structurally complex loci may have helped crop plants to 

 adapt to new selective regimes in agricultural ecosystems.},

keywords = {Agricultural Genetics, Genomics, Plant Breeding, Plant genetics},

pubstate = {published},

tppubtype = {article}

}

@article{WOS:001337849500001,

title = {MRI-Seed-Wizard: combining deep learning algorithms with magnetic  resonance imaging enables advanced seed phenotyping},

author = {Iaroslav Plutenko and Volodymyr Radchuk and Simon Mayer and Peter Keil and Stefan Ortleb and Steffen Wagner and Volker Lehmann and Hardy Rolletschek and Ljudmilla Borisjuk},

doi = {10.1093/jxb/erae408},

issn = {0022-0957},

year  = {2024},

date = {2024-10-01},

urldate = {2024-10-01},

journal = {JOURNAL OF EXPERIMENTAL BOTANY},

volume = {76},

number = {2},

pages = {393-410},

keywords = {Automatic segmentation, Deep learning, DiP-Magdi, Grain phenotyping, Magnetic resonance imaging, Morphometry, Wheat},

pubstate = {published},

tppubtype = {article}

}