Frank M. Johannes

vafSOMA detects cell-layer-fixed somatic mutations in plants using tissue composition, improving mutation detection and rate estimation in bulk sequencing data.

This study presents a chromosome-scale genome assembly of Edelweiss, revealing its recent allotetraploid origin and localized subgenome dominance.

simSOMA links plant branching topology to meristem cell-lineage dynamics; in simulations, niche size and turnover drive fixation, while terminal organ growth produces most private low-frequency variants.

This study integrates 16 Arabidopsis thaliana DNA methylome datasets to identify common and stress-specific methylation responses across biotic and abiotic stress conditions.

This study shows brassinosteroids repress plant immunity by inducing DNA methylation and altering splicing of immune receptor genes through bHLH transcription factors.

This study analyzes genetic and epigenetic divergence in Arabidopsis thaliana Col-0 laboratory lineages over decades, revealing substantial divergence and functional consequences.

This study shows that GSNOR-dependent nitric oxide homeostasis aids recovery from repeated climate stress in Arabidopsis across generations, while its impairment leads to persistent stress responses.

The paper identifies centromeres as hotspots for spontaneous DNA methylation epimutations in Neurospora crassa, showing these changes are mitotically stable and occur much more frequently than genetic mutations.

The paper identifies somatic DNA methylation heterogeneity in Arabidopsis leaves and links it to transgenerational epimutation hotspots.

This study examines the transcriptomic responses of European beech to simulated future climate scenarios, finding stronger responses under the high-emission RCP8.5 scenario compared to the mitigation-focused RCP2.6.

This study shows that faster tree growth increases the annual rate of somatic epimutations at CG dinucleotides, likely due to higher cell division rates.

The paper corrects distance bias in single-cell co-accessibility and deep-learning chromatin interaction predictions using multi-component power-law penalties informed by Gaussian mixture modeling and polymer-physics scaling.

The paper estimates parameters of somatic mutation evolution in long-lived plants using cell-layer-enriched DNA sequencing data.

The paper tracks DNA methylation across generations in Arabidopsis lineages to identify a genetic modifier that increases epimutation rates and supports a punctuated-equilibrium model of methylation evolution.

The paper identifies cell-type-specific cis-regulatory variants in maize using single-cell genomics and population genetics, revealing their role in local adaptation and flowering.

The paper shows branching architecture in trees suppresses somatic mutation accumulation, reducing mutation burden as effectively as lowering mutation rates.

The paper shows that the yearly rate of somatic mutations and epimutations in trees scales inversely with generation time, following the same allometric power law as in mammals.

The paper shows that multi-generational exposure to biotic stress increases epimutation rates in Arabidopsis, mediated by ROS1, affecting low-methylation genes.

The paper models somatic epigenetic drift during shoot branching, showing that cell lineage independence leads to DNA methylation heterogeneity in the shoot apical meristem.

GenomicLinks predicts 3D chromatin loops in maize by identifying sequence features associated with transcription factor binding motifs, validated using single-cell co-accessibility data.

This study shows that parental pericentromeric methylation patterns drive methylome and transcriptome changes in hybrids, contributing to heterosis in Arabidopsis.

This paper introduces a Recursive Convolutional Neural Network for predicting gene expression from histone modification intensity, achieving better performance with fewer parameters.

AlphaBeta estimates epimutation rates and spectra from DNA methylation data in plants, showing conserved epimutation landscapes and providing a molecular clock for tree age-dating.

MethylStar is a pre-processing pipeline for WGBS data that improves speed and memory efficiency compared to existing tools.

The paper quantifies age-related somatic mutations and epimutations in a wild Populus trichocarpa tree over 330 years, showing lower mutation rates than annuals and distinct epimutation origins.

METHimpute constructs complete methylomes from low-coverage WGBS data using a Hidden Markov Model, achieving high accuracy at 6X coverage compared to 60X.

The paper trains SVM models on sRNA sequencing data to identify sequence features determining AGO affinity, leading to a tool for classifying sRNA function in plants.

The paper shows that small RNAs in apomictic dandelion lineages reflect drought stress and salicylic acid treatment from two generations ago, indicating transgenerational epigenetic effects.