Biology subjects

Andersson, R.

Publications and source records attributed to Andersson, R..

At least 19 recordsLinked to original sources

bioRxiv2026

Metabolic disease-relevant stimuli unmask context-dependent genetic regulation of cardiometabolic loci in human adipocytes

Genome-wide association studies (GWAS) have identified thousands of loci associated with cardiometabolic disease, yet translating these associations into regulatory mechanisms, effector genes, and cellular programs remains a major challenge. A key limitation is that genetic effects are often highly context dependent, varying across cell states and environmental conditions that are difficult to model at scale. Here, we leverage CellGenBank, a population-scale biobank of primary human adipose-derived mesenchymal stem cells (AMSCs), to implement a multi-donor cell village in vitro system to map cardiometabolic disease genetic variation across adipocyte differentiation and metabolic stress conditions. We pooled AMSCs from 118 donors into multiplexed villages, differentiated them toward adipocytes, and profiled chromatin accessibility and gene expression using single-nucleus multiome sequencing under four disease-relevant conditions: basal, elevated free fatty acids, low glucose, and hypoxia. By combining with genetic demultiplexing, we quantify how regulatory element activity, gene expression, and higher-order cellular programs are modulated by both genotype and environmental context. Across conditions, we identify widespread context-specific cis-regulatory effects, including expression and chromatin accessibility quantitative trait loci that are masked in baseline states. Genetic effects frequently converge on coordinated transcriptional programs linked to lipid metabolism, insulin responsiveness, and stress adaptation, enabling the identification of cellular program QTLs that bridge variants, genes, and disease-relevant phenotypes. Integration with cardiometabolic GWAS reveals enhanced colocalization in condition- and state-resolved analyses, highlighting the importance of modeling environmental context to resolve disease mechanisms. Together, our study establishes large-scale adipocyte cell villages as a powerful and generalizable framework to map the context-dependent regulatory architecture of cardiometabolic disease and provides a resource linking human genetic variation to adipocyte cellular programs.

genomics↗

bioRxiv2026

Time-resolved inference of gene regulatory networks underlying human cranial neural crest development suggests novel risk genes for orofacial clefting.

Cranial neural crest cells (CNCCs) play a central role in shaping the human head and face. Aberrant CNCC differentiation contributes to craniofacial birth defects, particularly non-syndromic cleft lip with or without cleft palate (nsCL/P), one of the most common congenital disorders. Although the number of genetic variants associated with this condition is steadily increasing, it remains challenging to determine if and how these variants may contribute to disease development. The majority of these variants lie within non-coding regulatory elements that govern cell-type and stage-specific gene expression, which is orchestrated by dynamic gene regulatory networks (GRNs). Despite extensive work in model organisms, a time-resolved, multi-omics perspective of GRNs controlling CNCC differentiation in a human system is still lacking. To fill this gap, we generated paired transcriptomic and chromatin accessibility data at four timepoints during in vitro differentiation of CNCCs derived from human induced pluripotent stem cells. Integrating these two modalities enabled time-resolved inference of GRNs and identification of dynamic regulatory relationships, including stage-specific roles of core transcription factors. Leveraging these time-resolved GRNs, we mapped 29 nsCL/P associated variants linked to 70 putative target genes, with 40 located outside the associated genomic loci, suggesting novel distal regulatory relationships. Integration of these data with complementary time-course scRNA-seq data revealed an ectomesenchymal-biased subpopulation of CNCCs as particularly sensitive to genetic variants associated with nsCL/P. We provide a time-resolved inference of GRN in human CNCC differentiation, allowing us to determine the dynamics of stage-specific core regulatory programs that are otherwise missed in analyses based on a single time snapshot. To our knowledge, the data represent the first multi-omics map of human CNCC with temporal resolution, which expands the understanding of early human craniofacial development, refines variant-to-gene assignment, prioritizes candidate risk genes and cell states relevant to nsCL/P. Our findings demonstrate the relevance of studying the dynamics upon differentiation rather than just one fixed timepoint and offer a valuable basis for further investigation of non-coding variation in CNCC-related disorders.

bioinformatics↗

bioRxiv2026

Mapping active cis-regulatory elements from transcription initiation events

Determining the activity of cis-regulatory elements (CREs) is essential for modeling gene regulation and interpreting genetic variation. Yet, current methods often lack the specificity to distinguish active regulation from permissive chromatin, the sensitivity to detect unstable enhancer RNAs, or the scalability required to profile limited input material and primary cells. Here, we introduce nucCAGE, a transcription start site (TSS) assay for profiling nuclear, capped RNAs, and PRIME, a computational framework for identifying active CREs from TSS data. Together, these methods increase sensitivity to low-abundance RNAs and enable robust detection of active regulatory elements across diverse contexts. Across multiple orthogonal functional and genetic benchmarks, including fine-mapped eQTLs, ClinVar variants, GWAS loci, and CRISPRi-tested elements, nucCAGE-derived PRIME predictions achieve superior recall compared to state-of-the-art methods while maintaining strong enrichment for phenotype-associated variation. Applying PRIME to the FANTOM5 dataset yields a comprehensive, cell-type-resolved atlas of active CREs that recapitulates known tissue-trait relationships. We demonstrate how this atlas can be used to nominate causal noncoding variants, linking immune-cell enhancer regulation of SMAD3 to asthma and NCOR2 to premature separation of placenta. Together, nucCAGE and PRIME provide a framework for high-sensitivity genome-wide discovery of active CREs and a resource for variant-to-function studies.

genomics↗

bioRxiv2025

Deep Learning links TP53 genotype to expression-defined transcriptional program in Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is a hematological cancer characterized by genetic diversity and poor clinical outcomes. Among various genetic mutations in AML, TP53 mutations have relatively low prevalence and present very dismal survival rates. While the genetic features of AML are well understood, the transcriptional programs associated with TP53 dysfunction are less clear, especially across different clinical groups. To fill this gap, we used deep learning on four bulk RNA-seq datasets grouped by p53 expression and a single-cell TARGET-seq dataset classified by TP53 genotype. The bulk data revealed disruptions in chromatin regulation, DNA repair, and immune pathways, with the low-p53 state showing activation of chemokine and interleukin signaling. In the single-cell data, deep learning classifiers successfully distinguished WT from multi-hit TP53-mutant cells, while heterozygous TP53 cells remained transcriptionally similar to WT. Comparing bulk and single-cell results, we found a strong positive correlation between p53-low expression states and TP53-inactive genotypes, linking the expression-based and mutation-based axes of p53 activity. Our study identifies a consistent TP53-related transcriptional signature that connects p53-low expression patterns with underlying TP53 AML.

bioinformatics↗

bioRxiv2025

Genome-wide rules of transcription factor cooperativity revealed through in silico binding site ablation

Transcription factor (TF) cooperativity plays a critical role in gene regulation. However, the underlying genomic rules remain unclear, calling for scalable methods to characterize the TF binding site (motif) syntax of regulatory elements. Here, we introduce DeepCompARE, a lightweight model paired with an in silico ablation (ISA) framework for genome-wide analysis of regulatory sequences. Our framework enables precise interpretation of the motif syntax governing chromatin accessibility, enhancer activity, and promoter function. We find that most TF motifs are pairwise independent, indicating a default additive behavior of TFs, and define a cooperativity score to quantify deviations from this baseline. This reveals synergy and redundancy as opposite effects along the same cooperative spectrum. TF redundancy is linked to promoter activity and broad expression, whereas TF synergy is associated with enhancer activity, physical interactions, and cell-type specificity. Our framework provides a quantitative model for TF cooperativity, offering new insights into gene regulatory logic.

bioinformatics↗

bioRxiv2024

Mapping enhancer-gene regulatory interactions from single-cell data

Mapping enhancers and their target genes in specific cell types is crucial for understanding gene regulation and human disease genetics. However, accurately predicting enhancer-gene regulatory interactions from single-cell datasets has been challenging. Here, we introduce a new family of classification models, scE2G, to predict enhancer-gene regulation. These models use features from single-cell ATAC-seq or multiomic RNA and ATAC-seq data and are trained on a CRISPR perturbation dataset including >10,000 evaluated element-gene pairs. We benchmark scE2G models against CRISPR perturbations, fine-mapped eQTLs, and GWAS variant-gene associations and demonstrate state-of-the-art performance at prediction tasks across multiple cell types and categories of perturbations. We apply scE2G to build maps of enhancer-gene regulatory interactions in heterogeneous tissues and interpret noncoding variants associated with complex traits, nominating regulatory interactions linking INPP4B and IL15 to lymphocyte counts. The scE2G models will enable accurate mapping of enhancer-gene regulatory interactions across thousands of diverse human cell types.

genetics↗

bioRxiv2023

Adaptation to an acid microenvironment promotes pancreatic cancer organoid growth and drug resistance in a p53-dependent manner

The harsh environments in poorly perfused tumor regions have been proposed to select for traits that may drive cancer aggressiveness. Here, we tested the hypothesis that tumor acidosis interacts with driver mutations to exacerbate cancer hallmarks, including drug resistance, in pancreatic cancer. We gradually adapted mouse organoids from normal pancreatic duct (mN) and early PDAC (mP, with KRAS G12V mutation and +/- p53 knockout), from pH 7.4 (physiological level) to 6.7, representing acidic tumor niches. Acid adaptation rewired organoid transcriptional activity, increased viability and, strikingly, increased Gemcitabine- and Erlotinib resistance. Importantly, this response only occurred in organoids expressing wild-type p53 and was most pronounced when acid-adapted cells were returned to physiological pH (mimicking increased perfusion or invasion). While the acid adaptation transcriptional change was overall not highly similar to that induced by drug adaptation of the organoids, acid adaptation induced expression of cytidine deaminase (Cda) and ribonucleotide reductase regulatory subunit M2 (Rrm2), both associated with Gemcitabine resistance, and inhibition of these proteins partially restored Gemcitabine sensitivity. Thus, adaptation to the acidic tumor microenvironment increases drug resistance even after cells leave this niche, and this is in part dependent on acid-adaptation-induced transcriptional upregulation of Cda and Rrm2.

cancer biology↗

bioRxiv2022

Transcription factor expression is the main determinant of variability in gene co-activity

Many genes are co-expressed and form genomic domains of coordinated gene activity. However, the regulatory determinants of domain co-activity remain unclear. Here, we leverage human individual variation in gene expression to characterize the co-regulatory processes underlying domain co-activity and systematically quantify their effect sizes. We employ transcriptional decomposition to extract from RNA expression data an expression component related to co-activity revealed by genomic positioning. This strategy reveals close to 1,500 co-activity domains, covering most expressed genes, of which the large majority are invariable across individuals. Focusing specifically on domains with high variability in co-activity reveals that contained genes have a higher sharing of eQTLs, a higher variability in enhancer interactions, and an enrichment of binding by variably expressed transcription factors compared to genes within non-variable domains. Through careful quantification of the relative contributions of regulatory processes underlying co-activity, we find transcription factor expression levels to be the main determinant of gene co-activity. Our results indicate that distal trans effects contribute more than local genetic variation to individual variation in co-activity domains.

bioinformatics↗

bioRxiv2022

Transfer learning reveals sequence determinants of regulatory element accessibility

Dysfunction of regulatory elements through genetic variants is a central mechanism in the pathogenesis of disease. To better understand disease etiology, there is consequently a need to understand how DNA encodes regulatory activity. Deep learning methods show great promise for modeling of biomolecular data from DNA sequence but are limited to large input data for training. Here, we develop ChromTransfer, a transfer learning method that uses a pre-trained, cell-type agnostic model of open chromatin regions as a basis for fine-tuning on regulatory sequences. We demonstrate superior performances with ChromTransfer for learning cell-type specific chromatin accessibility from sequence compared to models not informed by a pre-trained model. Importantly, ChromTransfer enables fine-tuning on small input data with minimal decrease in accuracy. We show that ChromTransfer uses sequence features matching binding site sequences of key transcription factors for prediction. Together, these results demonstrate ChromTransfer as a promising tool for learning the regulatory code.

bioinformatics↗

bioRxiv2021

Promoter sequence and architecture determine expression variability and confer robustness to genetic variants

Genetic and environmental exposures cause variability in gene expression. Although most genes are affected in a population, their effect sizes vary greatly, indicating the existence of regulatory mechanisms that could amplify or attenuate expression variability. Here, we investigate the relationship between the sequence and transcription start site architectures of promoters and their expression variability across human individuals. We find that expression variability can be largely explained by a promoters DNA sequence and its binding sites for specific transcription factors. We show that promoter expression variability reflects the biological process of a gene, demonstrating a selective trade-off between stability for metabolic genes and plasticity for responsive genes and those involved in signaling. Promoters with a rigid transcription start site architecture are more prone to have variable expression and to be associated with genetic variants with large effect sizes, while a flexible usage of transcription start sites within a promoter attenuates expression variability and limits genotypic effects. Our work provides insights into the variable nature of responsive genes and reveals a novel mechanism for supplying transcriptional and mutational robustness to essential genes through multiple transcription start site regions within a promoter.

genomics↗

bioRxiv2021

hyperTRIBER: a flexible R package for the analysis of differential RNA editing

AO_SCPLOWBSTRACTC_SCPLOWRNA editing by ADAR (adenosine deaminase acting on RNA) is gaining an increased interest in the field of post-transcriptional regulation. Fused to an RNA-binding protein (RBP) of interest, the catalytic activity of ADAR results in A-to-I RNA edits, whose identification will determine RBP-bound RNA transcripts. However, the computational tools available for their identification and differential RNA editing statistical analysis are limited or too specialised for general-purpose usage. Here we present hyperTRIBER, a flexible suite of tools, wrapped into a convenient R package, for the detection of differential RNA editing. hyperTRIBER is applicable to complex scenarios and experimental designs, and provides a robust statistical framework allowing for the control for coverage of reads at a given base, the total expression level and other co-variates. We demonstrate the capabilities of our approach on HyperTRIBE RNA-seq data for the detection of bound RNAs by the N6-methyladenosine (m6A) reader protein ECT2 in Arabidopsis roots. We show that hyperTRIBER finds edits with a high statistical power, even where editing proportions and RNA transcript expression levels are low, together demonstrating its usability and versatility for analysing differential RNA editing.

bioinformatics↗

bioRxiv2021

The Arabidopsis m6A-binding proteins ECT2 and ECT3 bind largely overlapping mRNA target sets and influence target mRNA abundance, not alternative polyadenylation

Gene regulation via N6-methyladenosine (m6A) in mRNA involves RNA-binding proteins that recognize m6A via a YT521-B homology (YTH) domain. The plant YTH domain proteins ECT2 and ECT3 act genetically redundantly in stimulating cell proliferation during organogenesis, but several fundamental questions regarding their mode of action remain unclear. Here, we use HyperTRIBE (targets of RNA-binding proteins identified by editing) to show that most ECT2 and ECT3 targets overlap, with only few examples of preferential targeting by either of the two proteins. HyperTRIBE in different mutant backgrounds also provides direct views of redundant and specific target interactions of the two proteins. We also show that contrary to conclusions of previous reports, ECT2 does not accumulate in the nucleus. Accordingly, inactivation of ECT2, ECT3 and their surrogate ECT4 does not change patterns of polyadenylation site choice in ECT2/3 target mRNAs, but does lead to lower steady state accumulation of target mRNAs. In addition, mRNA and microRNA expression profiles show indications of stress response activation in ect2/ect3/ect4 mutants, likely via indirect effects. Thus, previous suggestions of control of alternative polyadenylation by ECT2 are not supported by evidence, and ECT2 and ECT3 act largely redundantly to regulate target mRNA, including its abundance, in the cytoplasm.

molecular biology↗

bioRxiv2021

Endogenous retroviruses co-opted into divergently transcribed regulatory elements shape the regulatory landscape of embryonic stem cells

Transposable elements are an abundant source of transcription factor binding sites and favorable genomic integration may lead to their recruitment by the host genome for gene regulatory functions. However, it is unclear how frequent co-option of transposable elements as regulatory elements is, to which regulatory programs they contribute and how they compare to regulatory elements devoid of transposable elements. Here, we report a transcription initiation-centric, in-depth characterization of the transposon-derived regulatory landscape of mouse embryonic stem cells. We demonstrate that a substantial number of transposable elements, in particular endogenous retroviral elements, carry open chromatin regions that are divergently transcribed into unstable RNAs in a cell-type specific manner, and that these elements contribute to a sizable proportion of active enhancers and gene promoters. We further show that transposon subfamilies contribute differently and distinctly to the pluripotency regulatory program through their repertoires of transcription factor binding sites, shedding light on the formation of regulatory programs and the origins of regulatory elements.

genomics↗

bioRxiv2021

Principles of mRNA targeting and regulation via the Arabidopsis m6A-binding proteins ECT2 and ECT3

Specific recognition of N6-methyladenosine (m6A) in mRNA by RNA-binding proteins containing a YT521-B homology (YTH) domain is important in eukaryotic gene regulation. The Arabidopsis YTH-domain protein ECT2 is thought to bind to mRNA at URU(m6A)Y sites, yet RR(m6A)CH is the canonical m6A consensus site in all eukaryotes and ECT2 functions require m6A binding activity. Here, we apply iCLIP (individual-nucleotide resolution cross-linking and immunoprecipitation) and HyperTRIBE (targets of RNA-binding proteins identified by editing) to define high-quality target sets of ECT2, and analyze the patterns of enriched sequence motifs around ECT2 crosslink sites. Our analyses show that ECT2 does in fact bind to RR(m6A)CH. Pyrimidine-rich motifs are enriched around, but not at m6A-sites, reflecting a preference for N6-adenosine methylation of RRACH/GGAU islands in pyrimidine-rich regions. Such motifs, particularly oligo-U and UNUNU upstream of m6A sites, are also implicated in ECT2 binding via its intrinsically disordered region (IDR). Finally, URUAY-type motifs are enriched at ECT2 crosslink sites, but their distinct properties suggest function as sites of competition between binding of ECT2 and as yet unidentified RNA-binding proteins. Our study provides coherence between genetic and molecular studies of m6A-YTH function in plants, and reveals new insight into the mode of RNA recognition by YTH-domain-containing proteins.

molecular biology↗

bioRxiv2020

Differential role of cytosolic Hsp70s in longevity assurance and protein quality control

ABSTRACT70 kDa heat shock proteins (Hsp70) are essential chaperones of the protein quality control network; vital for cellular fitness and longevity. The four cytosolic Hsp70’s in yeast, Ssa1-4, are thought to be functionally redundant but the absence of Ssa1 and Ssa2 causes a severe reduction in cellular reproduction and accelerates replicative aging. In our efforts to identify which Hsp70 activities are most important for longevity assurance, we systematically investigated the capacity of Ssa4 to carry out the different activities performed by Ssa1/2 by overproducing Ssa4 in cells lacking these Hsp70 chaperones. We found that Ssa4, when overproduced in cells lacking Ssa1/2, rescued growth, mitigated aggregate formation, restored spatial deposition of aggregates into protein inclusions, and promoted protein degradation. In contrast, Ssa4 overproduction in the Hsp70 deficient cells failed to restore the recruitment of the disaggregase Hsp104 to misfolded/aggregated proteins, to fully restore clearance of protein aggregates, and to bring back the formation of the nucleolus-associated aggregation compartment. Exchanging the nucleotide-binding domain of Ssa4 with that of Ssa1 suppressed this ‘defect’ of Ssa4. Interestingly, Ssa4 overproduction extended the short lifespan of ssa1Δ ssa2Δ mutant cells to a lifespan comparable to, or even longer than, wild type cells, demonstrating that Hsp104-dependent aggregate clearance is not a prerequisite for longevity assurance in yeast.AUTHOR SUMMARY All organisms have proteins that network together to stabilize and protect the cell throughout its lifetime. One of these types of proteins are the Hsp70s (heat shock protein 70). Hsp70 proteins take part in folding other proteins to their functional form, untangling proteins from aggregates, organize aggregates inside the cell and ensure that damaged proteins are destroyed. In this study, we investigated three closely related Hsp70 proteins in yeast; Ssa1, 2 and 4, in an effort to describe the functional difference of Ssa4 compared to Ssa1 and 2 and to answer the question: What types of cellular stress protection are necessary to reach a normal lifespan? We show that Ssa4 can perform many of the same tasks as Ssa1 and 2, but Ssa4 doesn’t interact in the same manner as Ssa1 and 2 with other types of proteins. This leads to a delay in removing protein aggregates created after heat stress. Ssa4 also cannot ensure that misfolded proteins aggregate correctly inside the nucleus of the cell. However, this turns out not to be necessary for yeast cells to achieve a full lifespan, which shows us that as long as cells can prevent aggregates from forming in the first place, they can reach a full lifespan.Competing Interest StatementD. Ö. is employed by AstraZeneca Mölndal, Sweden F.E. is employed by AstraZeneca Mölndal, Sweden S.H. is employed by Cochlear Nordic AB, Mölnlycke, SwedenView Full Text

molecular biology↗

bioRxiv2018

The GBAF chromatin remodeling complex binds H3K27ac and mediates enhancer transcription

H3K27ac is associated with regulatory active enhancers, but its exact role in enhancer function remains elusive. Using mass spectrometry-based interaction proteomics, we identified the Super Elongation Complex (SEC) and GBAF, a non-canonical GLTSCR1L- and BRD9-containing SWI/SNF chromatin remodeling complex, to be major interactors of H3K27ac. We systematically characterized the composition of GBAF and the conserved GLTSCR1/1L GiBAF-domain, which we found to be responsible for GBAF complex formation and GLTSCR1L nuclear localization. Inhibition of the bromodomain of BRD9 revealed interaction between GLTSCR1L and H3K27ac to be BRD9-dependent and led to GLTSCR1L dislocation from its preferred binding sites at H3K27ac-associated enhancers. GLTSCR1L disassociation from chromatin resulted in genome-wide downregulation of enhancer transcription while leaving most mRNA expression levels unchanged, except for reduced mRNA levels from loci topologically linked to affected enhancers. Our results indicate that GBAF is an enhancer-associated chromatin remodeler important for transcriptional and regulatory activity of enhancers.\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=142 HEIGHT=200 SRC=\"FIGDIR/small/445148_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (32K):\norg.highwire.dtl.DTLVardef@10c54dborg.highwire.dtl.DTLVardef@9730dforg.highwire.dtl.DTLVardef@9985eorg.highwire.dtl.DTLVardef@1f26844_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2018

CAGEfightR: Cap Analysis of Gene Expression (CAGE) in R/Bioconductor

We developed the CAGEfightR R/Biconductor-package for analyzing CAGE data. CAGEfightR allows for fast and memory efficient identification of transcription start sites (TSSs) and predicted enhancers. Downstream analysis, including annotation, quantification, visualization and TSS shape statistics are implemented in easy-to-use functions. The package is freely available at https://bioconductor.org/packages/CAGEfightR

bioinformatics↗

bioRxiv2017

Transcription start site analysis reveals widespread divergent transcription in D. melanogaster and core promoter encoded enhancer activities

Mammalian gene promoters and enhancers share many properties. They are composed of a unified promoter architecture of divergent transcripton initiation and gene promoters may exhibit enhancer function. However, it is currently unclear how expression strength of a regulatory element relates to its enhancer strength and if the unifying architecture is conserved across Metazoa. Here we investigate the transcription initiation landscape and its associated RNA decay in D. melanogaster. Surprisingly, we find that the majority of active gene-distal enhancers and a considerable fraction of gene promoters are divergently transcribed. We observe quantitative relationships between enhancer potential, expression level and core promoter strength, providing an explanation for indirectly related histone modifications that are reflecting expression levels. Lowly abundant unstable RNAs initiated from weak core promoters are key characteristics of gene-distal developmental enhancers, while the housekeeping enhancer strengths of gene promoters reflect their expression strengths. The different layers of regulation mediated by gene-distal enhancers and gene promoters are also reflected in chromatin interaction data. Our results suggest a unified promoter architecture of many D. melanogaster regulatory elements, that is universal across Metazoa, whose regulatory functions seem to be related to their core promoter elements.

genomics↗