bioRxiv Science⌕ Search

Biology subjects

Dahlberg, J.

Publications and source records attributed to Dahlberg, J..

11 recordsLinked to original sources

Resolving thyroid lineage cell trajectories merging into a dual endocrine gland in mammals

The thyroid has a remarkable evolution, first appearing in invertebrate chordates as an integral exocrine constituent of the pharyngeal endostyle that is transformed into an endocrine gland during metamorphosis in basal vertebrates. In mammals, the thyroid acquires a second endocrine cell type, calcitonin-producing C-cells, which for long were inferred a neural crest origin, shuttled to the embryonic thyroid by the ultimobranchial bodies. However, recent lineage tracing experiments firmly establish these neuroendocrine cells also derive from foregut endoderm. Key questions remaining unanswered are how thyroid primordia independently develop and, unlike in all non-mammalian vertebrates, merge into a dual endocrine organ. Here, by leveraging a single-cell transcriptome atlas derived from mouse pharyngeal endoderm and its subsequent cell fates, we characterize the global gene expression profile of thyroid- and ultimobranchial-derived progenitor cells and identify comprehensive gene regulatory networks of lineage-specific transcription factors and novel target genes predicted to differentially regulate cell proliferation, plasticity and differentiation during development. Spatiotemporal analyses reveal C-cell precursors are triggered to undergo epithelial-mesenchymal transition (EMT) and cell-autonomously down-regulate collagen IV and degrade laminin that delineates the ultimobranchial body epithelium. However, the EMT program is not fully deployed until both cell lineages are mixed and propagate conjointly thus forming the typical thyroid histoarchitecture of follicles and parafollicular C-cells, every follicle/C-cell unit being enveloped by a renewed basement membrane. Mixed-type thyroid carcinoma recapitulates a synchronous lineage growth pattern but only the neuroendocrine tumor cells are able to escape the compound follicle boundaries and become invasive adopting a C-cell precursor-like migratory phenotype.

developmental biology↗

Development and evaluation of a cost-effective, mid-density SNP array as a sorghum community genotyping resource

The development of accessible and cost-effective genotyping platforms is essential to accelerate genetic gain in crop improvement. To address the U.S. sorghum communitys need for a standardized, mid-density genotyping resource, we developed and validated a targeted single-nucleotide polymorphism (SNP) array using the PlexSeq next-generation sequencing (NGS) platform. The resulting genotyping array includes 2,421 SNPs spanning all ten Sorghum bicolor chromosomes and integrates trait-linked and quality control markers selected by public and private stakeholders. Genotyping 2,726 diverse accessions, including the Sorghum Association Panel (SAP), demonstrated high call rates (>90% for most samples and markers), low missing data, and accurate resolution of population structure consistent with prior whole-genome studies. In comparative genomic prediction analyses, the mid-density array performed equivalently to high-density genotype-by-sequencing (GBS) platforms for key traits such as grain yield and plant height across multi-environment trials. Designed for broad utility in breeding pipelines, the array enables marker-assisted selection, genomic prediction, identity verification, and germplasm quality control. Moreover, its adoption by the USDA National Plant Germplasm System facilitates the curation of genebanks and the management of core collections. This community-driven genotyping platform offers a scalable, reproducible, and customizable tool to support molecular breeding in sorghum and underscores the value of targeted marker systems in resource-optimized crop improvement programs.

plant biology↗

Multi-season analysis reveals hundreds of drought-responsive genes in sorghum

Persistent drought affects global crop production and is becoming more severe in many parts of the world in recent decades. Deciphering how plants respond to drought will facilitate the development of flexible mitigation strategies. Sorghum bicolor L. Moench (sorghum), a major cereal crop and an emerging bioenergy crop, exhibits remarkable resilience to drought. To better understand the molecular traits that underlie sorghums remarkable drought tolerance, we undertook a large-scale sorghum gene expression profiling effort, totaling nearly 1,500 transcriptome profiles, across a 3-year field study with replicated plots in Californias Central Valley. This study included time-resolved gene expression data from roots and leaves of two sorghum genotypes, BTx642 and RTx430, with different pre-flowering and post-flowering drought-tolerance adaptations under control and drought conditions. Quantification of genotype-specific drought tolerance effects was enabled by de novo sequencing, assembly, and annotation of both BTx642 and RTx430 genomes. These reference-quality genomes were used to construct a pan-gene set for characterizing conserved and genotype-specific expression. By integrating time-resolved transcriptomic responses to drought in the field across three consecutive years, we identified a set of drought-responsive genes that responded similarly in all three years of our field study. This expansive dataset represents a unique resource for sorghum and drought research communities and provides a methodological framework for the integration of multi-faceted time-resolved transcriptomic datasets.

genomics↗

Single-Cell Protein Interactomes by the Proximity Network Assay

Cellular functions depend on dynamic interactions of proteins and their spatial organisation. While transcriptomic and proteomic methods of molecular parts-lists have enabled single-cell profiling based on abundance, scalable technologies allowing high-resolution measurements of protein organization and interactions at scale are lacking. Here we present the Proximity Network Assay (PNA), a DNA-based method for constructing three-dimensional nanoscale maps of 155 plasma membrane proteins in single cells without the use of optics. PNA employs barcoded antibodies and in situ rolling circle amplification to generate >40,000 spatial nodes per cell, which are linked through proximity-dependent gap-fill ligation and decoded by DNA sequencing forming single cell Proximity Networks. PNA captures abundance, self-clustering, and [~]12,000 pairwise colocalization relationships per single-cell, validating established protein interactions. This new modality provides a framework to uncover novel spatial biomarkers, reveal functional mechanisms, and advance translational studies in immunology, oncology, and cell therapy.

bioengineering↗

Molecular Pixelation: Single cell spatial proteomics by sequencing

The spatial distribution of cell surface proteins govern vital processes of the immune system such as inter-cell communication and mobility. However, tools for studying these at high multiplexing scale, resolution, and throughput needed to drive novel discoveries are lacking. We present Molecular Pixelation, a DNA-sequencing based method for single cell analysis to quantify protein abundance, spatial distribution, and colocalization of targeted proteins using Antibody Oligonucleotide Conjugates (AOCs). Relative locations of AOCs are inferred by sequentially associating these into local neighborhoods using DNA-pixels containing unique pixel identifier (UPI) sequences, forming >1,000 connected spatial zones per single cell in three dimensions. DNA-sequencing reads are computationally arranged into spatial single cell maps for 76 proteins without cell compartmentalization. By studying immune cell dynamics and using spatial statistics on graph representations of the data, previously known and novel patterns of protein spatial polarization and co-localization were found in chemokine-stimulated T-cells.

immunology↗

Metabolomic, photoprotective, and photosynthetic acclimatory responses to post-flowering drought in sorghum

Climate change is globally affecting rainfall patterns, necessitating the improvement of drought tolerance in crops. Sorghum bicolor is a drought-tolerant cereal capable of producing high yields under water scarcity conditions. Functional stay-green sorghum genotypes can maintain green leaf area and efficient grain filling in terminal post-flowering water deprivation, a period of ~10 weeks. To obtain molecular insights into these characteristics, two drought-tolerant genotypes, BTx642 and RTx430, were grown in control and terminal post-flowering drought field plots in the Central Valley of California. Photosynthetic, photoprotective, water dynamics, and biomass traits were quantified and correlated with metabolomic data collected from leaves, stems, and roots at multiple timepoints during drought. Physiological and metabolomic data was then compared to longitudinal RNA sequencing data collected from these two genotypes. The metabolic response to drought highlights the uniqueness of the post-flowering drought acclimation relative to pre-flowering drought. The functional stay-green genotype BTx642 specifically induced photoprotective responses in post-flowering drought supporting a putative role for photoprotection in the molecular basis of the functional stay-green trait. Specific genes are highlighted that may contribute to post-flowering drought tolerance and that can be targeted in crops to maximize yields under limited water input conditions. HighlightPathways contributing to the long-term maintenance of photosynthetic activity in terminal post-flowering drought are revealed by a comprehensive approach combining in-field photosynthetic physiological analysis, metabolomics, and transcriptomics.

plant biology↗

Pathway to Validate Gene Function in Key Bioenergy Crop, Sorghum bicolor

Determining gene function is an essential goal for the key bioenergy crop, Sorghum bicolor (L.) Moench - particularly for genes associated with its notable abiotic stress tolerances. However, detailed molecular understanding of the genes associated with those traits is limited. This was made clear in our in-depth transcriptome studies in sorghum, which indicated nearly 50% of its transcriptome is not annotated. In this report, we describe a full spectrum of tools needed to transform sorghum in order to validate and annotate genes. Efforts began with modifying a transformation method that uses the morphogenic genes Baby Boom and Wuschel2 (Ovule Development Protein2) to accelerate transformation speed and expand amenable genotypes. In our experience, transforming RTx430 without morphogenic genes requires ~18 to 21 weeks, compared with ~10 to 12 weeks to generate T0 plants using methods with morphogenic genes. Utilizing morphogenic genes also allowed for the transformation of several sorghum genotypes not previously transformed or historically recalcitrant to transformation, i.e., rapid cycling SC187, stay-green BTx642, BTx623 and sweet sorghum Ramada. In order to validate candidate genes via engineering, while simultaneously introducing the morphogenic genes, a co-transformation strategy, termed altruistic transformation, was developed. To accomplish editing of the target gene, phytoene desaturase, novel constructs were created that also included morphogenic genes. To enable full characterization of transformed plants, we adapted techniques to determine copy number and independence of events at high-throughput levels. Through these efforts, we created a complete pathway from Agrobacterium infection to high-throughput molecular genotyping that can be used to ascertain gene function and expedite basic genetic research in this widely-grown bioenergy crop plant.

plant biology↗

Drought shifts sorghum root metabolite and microbiome profiles and enriches the stress response factor pipecolic acid

Interactions between plants and their root-associated microbiome are important for determining host fitness during periods of stress. During drought, monoderm bacteria are more abundant in sorghum roots than in those of watered controls. Additionally, a reversion from monoderm to diderm dominance occurs in drought-stressed roots one week after rewatering. However, the mechanisms driving this rapid microbiome composition shift is currently unknown. To understand if changes in host metabolism are correlated with this shift, we employed 16S amplicon sequencing and metabolomics of root, rhizosphere, and soil at the peak of a preflowering drought and 24 hours after rewatering. The microbiomes of droughted roots, rhizospheres, and soils differed from watered controls, and shifts in bacterial composition were observed in root and rhizosphere 24 hours after rewatering, highlighting the rapid response of microbes to the cessation of drought. Next, we performed metabolomic profiling to identify putative drivers of this process. During drought, we observed a high abundance of abiotic stress response factors, including antioxidants, osmolytes, amino acids, and plant hormones. After rewatering, large shifts in metabolite abundances were observed in rhizosphere, whereas shifts in root and soil were subtle. In addition, pipecolic acid, a well-characterized systemic acquired resistance signalling compound, was enriched in roots and rhizosphere during drought. We found that exogenous application of pipecolic acid suppresses root growth via a systemic acquired resistance-independent mechanism. Collectively, these data provide a comprehensive characterization of metabolite shifts across three compartments during drought, and elucidate a potential role of pipecolic acid in the sorghum drought response. IMPORTANCEPlant-associated microbial communities shift in composition and contribute to host fitness during drought. In particular, Actinobacteria are enriched in plant roots and rhizosphere during drought. However, the mechanisms plants use to drive this shift are poorly understood. Here we apply a combination of bacterial and metabolite profiling in root, rhizosphere, and soil during drought and drought-recovery to investigate potential contributions of host metabolism towards shifts in bacterial composition. Our results demonstrate that drought alters metabolic profiles and that the response to rewatering differs between compartments; we identify drought-responsive metabolites that are highly correlated with Actinobacteria abundance. Furthermore, our study reports for the first time that pipecolic acid is a drought-enriched metabolite in sorghum roots. We demonstrate that exogenous application of pipecolic acid is able to provoke one of the classic drought responses in roots, root growth suppression, and that this activity functions independently from the systemic acquired resistance pathway.

plant biology↗

De novo assembly of two Swedish genomes reveals missing segments from the human GRCh38 reference and improves variant calling of population-scale sequencing data

We have performed de novo assembly of two Swedish genomes using long-read sequencing and optical mapping, resulting in total assembly sizes of nearly 3 Gb and hybrid scaffold N50 values of over 45 Mb. A further analysis revealed over 10 Mb of sequences absent from the human GRCh38 reference in each individual. Around 6 Mb of these novel sequences (NS) are shared with a Chinese personal genome. The NS are highly repetitive, have elevated GC-content and are primarily located in centromeric or telomeric regions. A BLAST search showed that 31% of the NS are different from any sequences deposited in nucleotide databases. The remaining NS correspond to human (62%) or primate (6%) nucleotide entries, while 1% of hits show the highest similarity to other species, including mouse and a few different classes of parasitic worms. Up to 1 Mb of NS can be assigned to chromosome Y, and large segments are missing from GRCh38 also at chromosomes 14, 17 and 21. Inclusion of these novel sequences into the GRCh38 reference radically improves the alignment and variant calling of whole-genome sequencing data at several genomic loci. Through a re-analysis of 200 samples from a Swedish population-scale sequencing project, we obtained over 75,000 putative novel SNVs per individual when using a custom version of GRCh38 extended with 17.3 Mb of NS. In addition, about 10,000 false positive SNV calls per individual were removed from the GRCh38 autosomes and sex chromosomes in the re-analysis, with some of them located in protein coding regions.

genomics↗

Arteria: An automation system for a sequencing core facility

Arteria is an automation system aimed at sequencing core facilities. It is built on existing open source technologies, with a modular design allowing for a community-driven effort to create plug-and-play micro-services. Herein we describe the Arteria system and elaborate on the underlying conceptual framework. The Arteria system breaks down into three conceptual levels; orchestration, process and execution. At the orchestration level it utilizes an event-based model of automation. It models processes, e.g. the steps involved in processing sequencing data, as workflows and executes these in a micro-service based environment. This creates a system which is both flexible and scalable. The Arteria Project code is available as open source software at http://www.github.com/arteria-project.

bioinformatics↗

SweGen: A whole-genome map of genetic variability in a cross-section of the Swedish population

Here we describe the SweGen dataset, a high-quality map of genetic variation in the Swedish population. This data represents a basic resource for clinical genetics laboratories as well as for sequencing-based association studies, by providing information on the frequencies of genetic variants in a cohort that is well matched to national patient cohorts. To select samples for this study, we first examined the genetic structure of the Swedish population using high-density SNP-array data from a nation-wide population based cohort of over 10,000 individuals. From this sample collection, 1,000 individuals, reflecting a cross-section of the population and capturing the main genetic structure, were selected for whole genome sequencing (WGS). Analysis pipelines were developed for automated alignment, variant calling and quality control of the sequencing data. This resulted in a whole-genome map of aggregated variant frequencies in the Swedish population that we hereby release to the scientific community.

genetics↗