Biology subjects

Fiedler, J.

Publications and source records attributed to Fiedler, J..

7 recordsLinked to original sources

bioRxiv2025

A century of breeding has preserved genetic variation, accumulated favorable alleles, and shaped the Rht gene portfolio in North American spring wheat

Hard red spring wheat (HRSW) is an important market class of wheat in North America with a rich history of breeding. We genotyped 1,013 HRSW lines representing a century of breeding material using a SNP array and targeted KASP genotyping to assess the changes in genetic diversity and Rht genes in HRSW from North America. Results show that early breeding efforts broadened an initially narrow gene pool derived from a few founders and subsequently maintained the genetic diversity. Analysis of Rht genes revealed that Rht-D1b was the predominant semi-dwarf allele from introduction of the Green Revolution genes (Rht-B1 and Rht-D1) in 1960s until the FHB epidemics of 1990s, when most breeding programs shifted to Rht-B1b. However, adoption of Rht-B1b and Rht-D1b remains low in some regions of the Great Plains. The dwarf alleles at GA-sensitive Rht24 and Rht25 have persisted in the region at low frequencies before the introduction of Green Revolution genes and have increased in frequency in recent decades. We also analyzed the effect of Rht genes on plant height (PH) in the HRSW growing region and found that Rht-B1b or Rht-D1b results in [~]12% reduction in PH, which decreases to [~]9% in dry environments. Notably, combining dwarfing alleles at Rht24 and Rht25 reduced height by [~]6% in dry environments, suggesting an alternative approach for reducing PH. Our analysis also revealed significant genetic interactions between Rht-B1 and Rht25, as well as between Rht-D1 and Rht24, which could help fine-tune PH for different environments by employing appropriate Rht combinations. Furthermore, our results demonstrate positive selection for photoperiod sensitivity in recent decades, particularly in high-latitude regions. This study provides a valuable genomic resource, and the findings enhance our understanding of past breeding efforts while offering insights to guide future plant breeding strategies.

plant biology↗

bioRxiv2024

Decoding auditory working memory content from EEG aftereffects of auditory-cortical TMS

Working memory (WM), short term maintenance of information for goal directed behavior, is essential to human cognition. Identifying the neural mechanisms supporting WM is a focal point of neuroscientific research. One prominent theory hypothesizes that WM content is carried in "activity-silent" brain states involving short-term synaptic changes. Information carried in such brain states could be decodable from content-specific changes in responses to unrelated "impulse stimuli". Here, we used single-pulse transcranial magnetic stimulation (spTMS) as the impulse stimulus and then decoded content maintained in WM from EEG using multivariate pattern analysis (MVPA) with robust non-parametric permutation testing. The decoding accuracy of WM content significantly enhanced after spTMS was delivered to the posterior superior temporal cortex during WM maintenance. Our results show that WM maintenance involves brain states, which are activity silent relative to other intrinsic processes visible in the EEG signal.

neuroscience↗

bioRxiv2024

Genomes of Aegilops umbellulata provide new insights into unique structural variations and genetic diversity in the U-genome for wheat improvement

Aegilops spp. serve as an important reservoir for novel sources of resistance or tolerance to biotic and abiotic stresses. To harness this reservoir, we have generated a high-quality chromosome-level genome assembly of an Ae. umbellulata accession PI 554389 using a combination of PacBio HiFi, Oxford nanopore, and chromosome conformation capture (Hi-C) sequencing technologies and resequenced 20 Ae. umbellulata genomes using Illumina sequencing. We assembled a 4.20 Gb genome spanned over seven chromosomes, rich in repetitive elements ([~]84%), achieving a QV of 59.54 with 98.14% completeness. The phylogenetic analysis places the U-genome with D-lineage, but major and distinct rearrangements were revealed in the U-genome. Unique transposon landscape of diploid U-genome and complex chromosomal rearrangements, most prominently in 4U and 6U chromosomes uncovered a distinct evolutionary trajectory of Ae. umbellulata. Additionally, the resequencing of geographically and morphologically diverse Ae. umbellulata accessions revealed three distinctive evolutionary sub-populations. Resequencing also identified six new haplotypes for Lr9, the first leaf rust resistance gene introgressed and cloned from Ae. umbellulata. These genomics resources along with high levels of resistance in the resequenced accessions against five devastating wheat diseases affirmed the genetic potential of Ae. umbellulata for wheat improvement.

plant biology↗

bioRxiv2023

SGLT2 inhibitors attenuate endothelial to mesenchymal transition and cardiac fibroblast activation

Beneficial effects of sodium glucose co-transporter 2 inhibitors (SGLT2is) in cardiovascular diseases have been extensively reported leading to the inclusion of these drugs in the treatment guidelines for heart failure. However, molecular actions especially on non-myocyte cells remain uncertain. We observed dose-dependent inhibitory effects of two SGLT2is, dapagliflozin (DAPA) and empagliflozin (EMPA), on inflammatory signaling in human umbilical vein endothelial cells (HUVECs). Proteomics analyses and subsequent enrichment analyses discovered profound effects of these SGLT2is on proteins involved in mitochondrial respiration and actin cytoskeleton. Validation in functional oxygen consumption measurements as well as tube formation and migration assays revealed strong impacts of DAPA. Considering that most influenced parameters played central roles in endothelial to mesenchymal transition (EndMT), we performed in vitro EndMT assays and identified substantial reduction of mesenchymal and fibrosis marker expression as well as changes in cellular morphology upon treatment with SGLT2is. In line, human cardiac fibroblasts (HCFs) exposed to DAPA showed less proliferation, reduced ATP production, and decelerated migration capacity while less extensive impacts were observed upon EMPA. Mechanistically, sodium proton exchanger 1 (NHE1) as well as sodium-myoinositol cotransporter (SMIT) and sodium-multivitamin cotransporter (SMVT) could be identified as relevant targets of SGLT2is in non-myocyte cardiovascular cells as validated by individual siRNA-knockdown experiments. In summary, we found comprehensive beneficial effects of SGLT2is on human endothelial cells and cardiac fibroblasts. The results of this study therefore support a distinct effect of selected SGLT2i on non-myocyte cardiovascular cells and grant further insights into potential molecular mode of action of these drugs.

pharmacology and toxicology↗

bioRxiv2021

Development of the Wheat Practical Haplotype Graph Database as a Resource for Genotyping Data Storage and Genotype Imputation

To improve the efficiency of high-density genotype data storage and imputation in bread wheat (Triticum aestivum L.), we applied the Practical Haplotype Graph (PHG) tool. The wheat PHG database was built using whole-exome capture sequencing data from a diverse set of 65 wheat accessions. Population haplotypes were inferred for the reference genome intervals defined by the boundaries of the high-quality gene models. Missing genotypes in the inference panels, composed of wheat cultivars or recombinant inbred lines genotyped by exome capture, genotyping-by-sequencing (GBS), or whole-genome skim-seq sequencing approaches, were imputed using the wheat PHG database. Though imputation accuracy varied depending on the method of sequencing and coverage depth, we found 93% imputation accuracy with 0.01x sequence coverage, which was only slightly lower than the accuracy obtained using the 0.5x sequence coverage (96.9%). Compared to Beagle, on average, PHG imputation was ~4% (p-value = 0.00027) more accurate, and showed 27% higher accuracy at imputing a rare haplotype introgressed from a wild relative into wheat. The reduced accuracy of imputation with GBS data (90.4%) is likely associated with the small overlap between GBS markers and the exome capture dataset, which was used for constructing PHG. The highest imputation accuracy was obtained with exome capture for the wheat D genome, which also showed the highest levels of linkage disequlibrium and proportion of identity-by-descent regions among accessions in our reference panel. We demonstrate that genetic mapping based on genotypes imputed using PHG identifies SNPs with a broader range of effect sizes that together explain a higher proportion of genetic variance for heading date and meiotic crossover rate compared to previous studies.

genomics↗

bioRxiv2018

CAMISIM: Simulating metagenomes and microbial communities

Shotgun metagenome data sets of microbial communities are highly diverse, not only due to the natural variation of the underlying biological systems, but also due to differences in laboratory protocols, replicate numbers, and sequencing technologies. Accordingly, to effectively assess the performance of metagenomic analysis software, a wide range of benchmark data sets are required. Here, we describe the CAMISIM microbial community and metagenome simulator. The software can model different microbial abundance profiles, multi-sample time series and differential abundance studies, includes real and simulated strain-level diversity, and generates second and third generation sequencing data from taxonomic profiles or de novo. Gold standards are created for sequence assembly, genome binning, taxonomic binning, and taxonomic profiling. CAMSIM generated the benchmark data sets of the first CAMI challenge. For two simulated multi-sample data sets of the human and mouse gut microbiomes we observed high functional congruence to the real data. As further applications, we investigated the effect of varying evolutionary genome divergence, sequencing depth, and read error profiles on two popular metagenome assemblers, MEGAHIT and metaSPAdes, on several thousand small data sets generated with CAMISIM. CAMISIM can simulate a wide variety of microbial communities and metagenome data sets together with truth standards for method evaluation. All data sets and the software are freely available at: https://github.com/CAMI-challenge/CAMISIM

bioinformatics↗

bioRxiv2017

Critical Assessment of Metagenome Interpretation - a benchmark of computational metagenomics software

In metagenome analysis, computational methods for assembly, taxonomic profiling and binning are key components facilitating downstream biological data interpretation. However, a lack of consensus about benchmarking datasets and evaluation metrics complicates proper performance assessment. The Critical Assessment of Metagenome Interpretation (CAMI) challenge has engaged the global developer community to benchmark their programs on datasets of unprecedented complexity and realism. Benchmark metagenomes were generated from ~700 newly sequenced microorganisms and ~600 novel viruses and plasmids, including genomes with varying degrees of relatedness to each other and to publicly available ones and representing common experimental setups. Across all datasets, assembly and genome binning programs performed well for species represented by individual genomes, while performance was substantially affected by the presence of related strains. Taxonomic profiling and binning programs were proficient at high taxonomic ranks, with a notable performance decrease below the family level. Parameter settings substantially impacted performances, underscoring the importance of program reproducibility. While highlighting current challenges in computational metagenomics, the CAMI results provide a roadmap for software selection to answer specific research questions.

bioinformatics↗