Biology subjects

Reif, J. C.

Publications and source records attributed to Reif, J. C..

9 recordsLinked to original sources

bioRxiv2026

Epistatic interaction of the genes Raw1 and Raw7 controls barb size and frequency in barley awn roughness

Awns of wild barley (Hordeum vulgare ssp. spontaneum L.) are rough by default due to silicified upward-oriented trichomes on the awns epidermis, forming a ratcheted surface, which is advantageous for seed dispersal and burial. Cultivated barley, however, may carry smooth awns covered by smaller barbs or lacking barbs completely. The gene Raw1 on chromosome 5H is a major factor controlling barley awn roughness and was shown to encode a LONG AND BARBED AWN1 (LABA1) homolog. Here we report, by using quantitative analysis of the barb trait, map-based cloning and Cas9-mediated gene knock-out, a second gene Raw7, located on barley chromosome 7H, encoding a putative two-component response regulator. We propose that Raw7 acts downstream of Raw1 in a cytokinin signaling pathway underlying cell cycle control in epidermal barb primordia cells. Raw1 and Raw7 show epistatic interaction, suggesting that Raw1 acts as the primary driver of barb initiation, while Raw7 modulates barb size and frequency. Our findings provide the foundation to study the selection and domestication history of the awn roughness trait in barley, and thus to dissect if awn roughness is providing an advantage in cultivated barley or if the trait persisted after domestication due to linkage drag. SummaryO_LIThe presence of silicified upward-oriented trichomes or barbs arising from the epidermis of barley awns is a prominent trait. They form a ratcheted surface which is advantageous for seed dispersal and burial and defense against herbivory. C_LIO_LIPrevious work identified Raw1 on chromosome 5H as a major determinant of awn roughness in barley. Here, we identify a second awn roughness gene, Raw7 on chromosome 7H, combining quantitative phenotyping of barb traits, map-based cloning and Cas9-mediated targeted mutagenesis for functional analyses. C_LIO_LIGenetic and functional evidence suggests a complex epistatic interaction in which Raw1 primarily drives barb formation and Raw7 fine-tunes endoreduplication-dependent epidermal cell expansion and patterning in barb primordia cells. Raw1 and Raw7 likely act in a cytokinin-dependent two-component signaling pathway, where Raw1 promotes local cytokinin activation and Raw7, a type-B response regulator, mediates downstream transcriptional responses. C_LIO_LIThe proposed pathway suggests additional undetected loci may contribute to awn roughness, and emerging barley pangenome and pan-transcriptome resources provide a framework to identify and functionally validate new candidates. C_LI

plant biology↗

bioRxiv2025

Powerful one-dimensional scan to detect heterotic QTL

To meet the growing global demand for food, increasing yields through heterosis in agriculture is crucial. A deep understanding of the genetic basis of heterosis has led to the development of a quantitative genetic framework that incorporates both dominance and epistatic effects. However, incorporating all pairwise epistatic interactions is computationally challenging due to the large sequencing depth and population sizes needed to uncover the genes behind complex traits. In this study, we developed hQTL-ODS, a one-dimensional scanning method that directly assesses the net contribution of each locus to heterosis. Simulations show that hQTL-ODS reduces computational time while offering higher power and lower false-positive rate. We applied this method to a population of 5,234 wheat hybrids with whole-genome sequenced profile, revealing key epistatic hubs that play a critical role in determining heterosis. Our findings offered valuable insights for improving breeding strategies to enhance crop yields.

genetics↗

bioRxiv2024

Large-scale multi-omics analyses identified root-microbiome associations underlying plant nitrogen nutrition

The microbiome determines the performance and fitness of the host plant. Nevertheless, the causal interaction between host genetic variation, gene regulation and the impact of the microbiome on the host phenotype remain unknown. Here we generated 1,341 paired root transcriptome, rhizosphere microbiome and root ionome samples and performed a multi-omics analyses of the host-microbe association at the root-soil interface using 175 rapeseeds (Brassica napus L.) resequenced ecotypes at two field environments. We observed the highest statistically explained variance for root nitrogen uptake among natural ionomic variation by overall transcriptome-wide gene expression and microbial abundance variation. Moreover, we identified significant genome-wide associations for 203 highly heritable amplicon sequence variants (ASVs) at multiple genetic loci regulated by eQTL hotspots associated with nitrogen metabolism components. These associations involved a central bacterial genus (Sphingopyxis), which plays a dominant role on gene regulatory effect on its variation regulated by eQTL hotspots. In addition, we performed high-throughput bacterial cultivation from rapeseed roots and subjected Sphingopyxis to whole genome sequencing. Finally, targeted metabolite profiling and confocal imaging assays demonstrated a host-microbiome regulatory effect on Sphingopyxis established by lateral root development and plant nitrogen nutrition. In summary, our integrative approach reveals the genetic basis of host-microbiome trait associations in the transcriptional, nutritional and environmental domains and suggests that the microbiome might have causal effects on root development with implications towards the breeding of nutrient-efficient crops.

plant biology↗

bioRxiv2023

A comprehensive overview and benchmarking analysis of fast algorithms for genome-wide association studies

Genome-wide association studies (GWAS) are a ubiquitous tool for identifying genetic variants associated with complex traits in structured populations. During the past 15 years, many fast GWAS algorithms based on a state-of-the-art model, namely the linear mixed model, have been published to cope with the rapidly growing data size. In this study, we provide a comprehensive overview and benchmarking analysis of 33 commonly used GWAS algorithms. Key mathematical techniques implemented in different algorithms were summarized. Empirical data analysis with 12 selected algorithms showed differences regarding the identification of quantitative trait loci (QTL) in several plant species. The performance of these algorithms evaluated in 10,800 simulated data sets with distinct population size, heritability and genetic architecture revealed the impact of these parameters on the power of QTL identification and false positive rate. Based on these results, a general guide on the choice of algorithms for the research community is proposed.

genetics↗

bioRxiv2023

Origin and evolution of the bread wheat D genome

Bread wheat (Triticum aestivum) is a globally dominant crop and major source of calories and proteins for the human diet. Compared to its wild ancestors, modern bread wheat shows lower genetic diversity caused by polyploidisation, domestication, and breeding bottlenecks1,2. Wild wheat relatives represent genetic reservoirs, harbouring diversity and beneficial alleles that have not been incorporated into bread wheat. Here, we establish and analyse pangenome resources for Tauschs goatgrass, Aegilops tauschii, the donor of the bread wheat D genome. This new pangenome facilitated the cloning of a disease resistance gene and haplotype analysis across a complex disease resistance locus, allowing us to discern alleles from paralogous gene copies. We also reveal the complex genetic composition and history of the bread wheat D genome, involving previously unreported contributions from genetically and geographically discrete Ae. tauschii subpopulations. Together, our results reveal the complex history of the bread wheat D genome and demonstrate the potential of wild relatives in crop improvement.

genomics↗

bioRxiv2023

Genomic unveiling of the diversity in grain protein and lysine content throughout a genebank collection of winter wheat

Globally, wheat (Triticum aestivum L.) is a major source of proteins in human nutrition despite its unbalanced amino acid composition. The low lysine content in the protein fraction of wheat can lead to protein-energy-malnutrition prominently in developing countries. A promising strategy to overcome this problem is to breed varieties which combine high protein content with high lysine content. Nevertheless, this requires the incorporation of yet undefined donor genotypes into pre-breeding programs. Genebank collections are suspected to harbor the needed genetic diversity. In the 1970s, a large-scale screening of protein traits was conducted for the wheat genebank collection in Gatersleben; however, this data has been poorly mined so far. In the present study, a large historical dataset on protein content and lysine content was curated and the corresponding adjusted entry means were calculated. High-quality phenotypic data of 558 accessions was leveraged by engaging four genomic prediction approaches. Based on the predicted phenotypes of 7,651 winter wheat accessions, few of them were recommended as donor genotypes due to suitable protein characteristic. Further investigation of the passport data suggested an association of the adjusted lysine content with the elevation of the collecting site. This publicly available information can facilitate future pre-breeding activities. HighlightHistorical data of lysine and protein content can be leveraged by engaging genomic prediction of an entire winter wheat genebank collection which enables to propose donor genotypes for pre-breeding.

genomics↗

bioRxiv2023

Heritable maize microbiomes contribute to local adaptation and host stress resilience

Beneficial interactions with microorganisms are pivotal for crop performance and resilience. However, it remains unclear how heritable the microbiome is with respect to the host plant genotype and to what extent host genetic mechanisms can modulate plant-microbe interactions in the face of environmental stress. Here, we surveyed the root and rhizosphere microbiome of 129 accessions of locally adapted Zea mays, sourced from diverse habitats and grown under control and different stress conditions. We quantified treatment and host genotype effects on the microbiome. Plant genotype and source environment were predictive of microbiome composition. Genome wide association analysis identified host genetic variants linked to both rhizosphere microbiome composition and source environment. We identified transposon insertions in a candidate gene linked to both the abundance of a keystone microbe Massilia and source total soil nitrogen, finding mutant plants to show a reduction in lateral root density. We conclude that locally adapted maize varieties exert patterns of genetic control on their root and rhizosphere microbiomes that follow variation in their home environments, consistent with a role in tolerance to prevailing stress.

genetics↗

bioRxiv2022

Genome-wide signatures of geographic expansion and breeding process in soybean

The clarification of genomic signatures left during evolutionary histories of crops is crucial for breeding varieties adapting to changing climate. Soybean, a leguminous crop, provides both plant oil and protein. Here, we analyzed genome sequences of 2,214 soybeans and proposed its evolutionary route, which includes four geographic paths, expansion of annual wild soybean (Glycine soja Sieb. & Zucc.) from Southern China, domestication in Central China, expansion of landrace (G. max (L.) Merr.), and local breeding. We observed that local adaptation of the wild and cultivated soybeans was largely independent, and that genetic introgression was mostly derived from sympatric rather than allopatric wild populations during the range expansion of soybean landraces. Range expansion and breeding processes were accompanied with positive selection of flowering-time genes including GmSPA3c as validated by knock-out mutants. Our study shed lights on the evolutionary history of soybean and provides valuable genetic resources for future breeding. TeaserThe expansion and selection history of soybean

genomics↗

bioRxiv2021

GiPS: Genomics-informed parent selection uncovers the breeding value of wheat genetic resources

The great efforts spent in the maintenance of past diversity in genebanks are rationalized by the potential role of plant genetic resources in future crop improvement - a concept whose practical implementation has fallen short of expectations. Here, we implement genomics-informed parent selection to expedite pre-breeding without discriminating against non-adapted germplasm. We collect dense genetic profiles for a large winter wheat collection and evaluate grain yield and resistance to yellow rust in representative coresets. Genomic prediction within and across genebanks identified the best parents for PGR x elite derived crosses that outyielded current elite cultivars in multiple field trials.

genomics↗