Biology subjects

Möller, S.

Publications and source records attributed to Möller, S..

3 recordsLinked to original sources

bioRxiv2021

Gene co-expression analyses of health(span) across multiple species

Health(span)-related gene clusters/modules were recently identified based on knowledge about the cross-species genetic basis of health, to interpret transcriptomic datasets describing health-related interventions. However, the cross-species comparison of health-related observations reveals a lot of heterogeneity, not least due to widely varying health(span) definitions and study designs, posing a challenge for the exploration of conserved healthspan modules and, specifically, their transfer across species. To improve the identification and exploration of conserved/transferable healthspan modules, here we apply an established workflow based on gene co-expression network analyses employing GEO/ArrayExpress data for human and animal models, and perform a comprehensive meta-analysis of the resulting modules related to health(span), yielding a small set of health(span) candidate genes, backed by the literature. For each experiment, WGCNA (weighted gene correlation network analysis) was thus used to infer modules of genes which correlate in their expression with a "health phenotype score" and to determine the most-connected (hub) genes for each such module, and their interactions. After mapping these hub genes to their human orthologs, 12 health(span) genes were identified in at least two species (ACTN3, ANK1, MRPL18, MYL1, PAXIP1, PPP1CA, SCN3B, SDCBP, SKIV2L, TUBG1, TYROBP, WIPF1), for which enrichment analysis by g:profiler finds an association with actin filament-based movement and associated organelles as well as muscular structures. We conclude that a meta-study of hub genes from co-expression network analyses for the complex phenotype health(span), across multiple species, can yield molecular-mechanistic insights and can direct experimentalists to further investigate the contribution of individual genes and their interactions to health(span).

genomics↗

bioRxiv2018

Pathway maps enable straightforward yet customized and semi-automated yet insightful analyses of omics data

To explore the molecular processes underlying some biological theme of interest based on public data, gene lists are used herein as input for the construction of annotated pathway maps, employing Cytoscape apps, and then high-throughput (\"omics\") gene expression data are overlaid onto these maps. Seeded with a published set of marker genes of the senescence-associated secretory phenotype and the genes of the cellular senescence KEGG pathway, a gene/protein interaction network and annotated clusters (a \"pathway map\") of cellular senescence are derived. The map can be amended, by adding some application-specific genes, and overlaid with gene expression data describing cellular senescence of fibroblasts and with disease-related gene expression data associated with prostate and pancreatic cancer, and with ischemic stroke, allowing insights into the role of cellular senescence in disease. Some gene expression data are derived from the \"Biomarker Benchmark repository\". The pathway map approach can be followed in principle for any biological theme of interest, fostering much-needed independence from the investigator-biased expert networks usually used for overlaying gene expression data.

genomics↗

bioRxiv2018

Analysis of human immunoglobulin VDJ and DJ rearrangements shows N region synthesis by concatenation of cytosine-rich strands preferentially originating from trimmed germline gene segments

The formation of non-templated (N) regions during immunoglobulin gene rearrangement is a major contributor to antibody diversity. To gain insights into the mechanisms behind this, we studied the nucleotide composition of N regions within 29,962 unique human VHDJH-rearrangements and 8,728 unique human DJH-rearrangements containing exactly one identifiable D-gene segment and thus two N regions, N1 and N2. We found a distinct decreasing content of cytosine (C) and increasing content of guanine (G) across each N region, suggesting that N regions are typically generated by concatenation of two 3-overhangs synthesized by addition of nucleoside triphosphates with a preference for dCTP. This challenges the general assumption that the terminal deoxynucleotidyl transferase favors dGTP in vivo. Furthermore, we found that the G and C gradients depended strongly on whether the germline gene segments were trimmed or not. Our data show that C-enriched N addition preferentially happens at trimmed 3-ends of VH-, D-, and JH-gene segments indicating a dependency of the transferase mechanism upon the nuclease mechanism.

immunology↗