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Biology subjects

Reiman, R.

Publications and source records attributed to Reiman, R..

5 recordsLinked to original sources

Diploid genome assembly of human fibroblast cell lines enables clone specific variant calling, improved read mapping and accurate phasing

Human cell lines are fundamental tools in biomedical research and are widely used in disease modeling, drug development, and many other domains. Here, we present chromosome-level, phased diploid genome assemblies of two popular human cell lines: the BJ foreskin fibroblast line and the IMR-90 fetal lung fibroblast line. Our high-quality assemblies, generated using long-read and Hi-C sequencing data, reveal substantial structural variation, including more than 50,000 insertions, deletions, duplications, and inversions compared to the recent T2T-CHM13v2.0 reference. Our assemblies provide detailed maps of genetic variation, enabling more accurate variant calling and the ability to phase reads when using newly generated or historical sequencing data on these cell lines or their derivatives. All assemblies and associated data have been made available as a resource for the research community. We envision that diploid genome assembly will become a cornerstone approach for personalized medicine in the near future.

genomics↗

Extracellular Vesicles heterogeneity through the lens of multiomics

Extracellular vesicles (EVs) are heterogenous in size, biogenesis, cargo and function. Beside small EVs, aggressive tumor cells release a population of particularly large EVs, namely large oncosomes (LO). This study provides the first resource of label-free quantitative proteomics of LO and small EVs obtained from distinct cancer cell types (prostate, breast, and glioma). This dataset was integrated with a SWATH Proteomic assay on LO, rigorously isolated from the plasma of patients with metastatic prostate cancer (PC). Proteins enriched in LO, which were identified also at the RNA level, and found in plasma LO significantly correlated with PC progression. Single EV RNA-Seq of the PC cell-derived LO confirmed some of the main findings from the bulk RNA-Seq, providing first evidence that single cell technologies can be successfully applied to EVs. This multiomics resource of cancer EVs can be leveraged for developing a multi-analyte approach for liquid biopsy.

cancer biology↗

A public resource of single cell transcriptomes and multiscale networks from persons with and without Alzheimer's disease

The emergence of technologies that can support high-throughput profiling of single cell transcriptomes offers to revolutionize the study of brain tissue from persons with and without Alzheimers disease (AD). Integration of these data with additional complementary multiomics data such as genetics, proteomics and clinical data provides powerful opportunities to link observed cell subpopulations and molecular network features within a broader disease-relevant context. We report here single nucleus RNA sequencing (snRNA-seq) profiles generated from superior frontal gyrus cortical tissue samples from 101 exceptionally well characterized, aged subjects from the Banner Brain and Body Donation Program in combination with whole genome sequences. We report findings that link common AD risk variants with CR1 expression in oligodendrocytes as well as alterations in peripheral hematological lab parameters, with these observations replicated in an independent, prospective cohort study of ageing and dementia. We also observed an AD-associated CD83(+) microglial subtype with unique molecular networks that encompass many known regulators of AD-relevant microglial biology, and which are associated with immunoglobulin IgG4 production in the transverse colon. These findings illustrate the power of multi-tissue molecular profiling to contextualize snRNA-seq brain transcriptomics and reveal novel disease biology. The transcriptomic, genetic, phenotypic, and network data resources described within this study are available for access and utilization by the scientific community.

genomics↗

Dynamic Transcriptomic Network Responses to Divergent Acute Exercise Challenges in Young Adults

Acute exercise elicits dynamic transcriptional changes that, when repeated, form the fundamental basis of adaptations in health, resilience, and performance. While moderate-intensity endurance training combined with conventional resistance training (traditional, TRAD) is often prescribed and recommended by public health guidance, high-intensity training combining maximal-effort intervals with intensive, limited-rest resistance training is a time-efficient alternative that may be used tactically (HITT) to seek whole body health benefits. Mechanisms of action of these distinct doses are incompletely characterized and have not been directly compared. We assessed transcriptome-wide responses in skeletal muscle and circulating extracellular vesicles (EVs) to a single exercise bout in young adults randomized to TRAD (n=21, 12M/9F, 22{+/-}3y) or HITT (n=19, 11M/8F, 22{+/-}2y). Next-generation sequencing captured small, long, and circular RNA in muscle and EVs. Analysis identified differentially expressed transcripts (|log2FC|>1, FDR[&le;]0.05) immediately (h0, EVs only), h3, and h24 post-exercise within and between exercise doses. Additionally, all apparently responsive transcripts (FDR<0.2) underwent singular value decomposition to summarize data structures into latent variables (LVs) to deconvolve molecular expression circuits and inter-regulatory relationships. LVs were compared across time and exercise dose. TRAD generally elicited a stronger, more consistent transcriptional response than HITT, but considerable overlap and key differences existed. Findings reveal shared and unique molecular responses to divergent exercise stimuli and lay groundwork toward establishing relationships between protein-coding genes and lesser-understood transcripts that serve regulatory roles in response to exercise. Future work should advance the understanding of these circuits and whether they repeat in other populations or following other types of exercise/stress. NEW AND NOTEWORTHYWe examined small and long transcriptomics in skeletal muscle and serum-derived extracellular vesicles before and after a single exposure to traditional combined exercise (TRAD) and high-intensity tactical training (HITT). Across 40 young adults, we found more consistent protein-coding gene responses to TRAD, whereas HITT elicited differential expression of microRNA enriched in brain regions. Follow-up analysis revealed relationships and temporal dynamics across transcript networks, highlighting potential avenues for research into mechanisms of exercise response and adaptation.

bioinformatics↗

The Foundational data initiative for Parkinsons disease (FOUNDIN-PD): enabling efficient translation from genetic maps to mechanism

The FOUNdational Data INitiative for Parkinsons Disease (FOUNDIN-PD) is an international collaboration producing fundamental resources for Parkinsons disease (PD). FOUNDIN-PD generated a multi-layered molecular dataset in a cohort of induced pluripotent stem cell (iPSC) lines differentiated to dopaminergic (DA) neurons, a major affected cell type in PD. The lines were derived from the Parkinsons Progression Markers Initiative study including participants with PD carrying monogenic PD (SNCA) variants, variants with intermediate effects and variants identified by genome-wide association studies and unaffected individuals. We generated genetic, epigenetic, regulatory, transcriptomic, and longitudinal cellular imaging data from iPSC-derived DA neurons to understand molecular relationships between disease associated genetic variation and proximate molecular events. These data reveal that iPSC-derived DA neurons provide a valuable cellular context and foundational atlas for modelling PD genetic risk. We have integrated these data into a FOUNDIN-PD data browser (https://www.foundinpd.org) as a resource for understanding the molecular pathogenesis of PD.

genomics↗