Biology subjects

Coussement, L.

Publications and source records attributed to Coussement, L..

2 recordsLinked to original sources

bioRxiv2022

Liver transcriptomic and methylomic analyses identify transcriptional MAPK regulation in facultative hibernation of Syrian hamster

Hibernation consist of alternating torpor/arousal phases, during which animals cope with repetitive hypothermia and ischemia-reperfusion. Due to limited transcriptomic and methylomic information for facultative hibernators, we here conducted RNA and whole genome bisulfite sequencing in liver of hibernating Syrian hamster (Mesocricetus auratus). Gene Ontology analysis was performed on 844 differentially expressed genes (DEGs) and confirmed the shift in metabolic fuel utilization, inhibition of RNA transcription and cell cycle regulation as found in seasonal hibernators. We show a so far unreported suppression of MAPK and PP1 pathways. Notably, hibernating hamsters showed upregulation of MAPK inhibitors (DUSPs and SPRYs) and reduced levels of MAPK induced transcription factors. Promoter methylation was found to modulate the expression of genes targeted by these transcription factors. In conclusion, we document gene regulation between hibernation phases, which may aid the identification of pathways and targets to prevent organ damage in transplantation or ischemia-reperfusion.

genomics↗

bioRxiv2022

MAGE enables population level RNAseq driven genotyping and (differential) allelic divergence detection in healthy kidney and carcinoma

Decreasing sequencing costs have instigated large-scale RNAseq experiments, yet genetic polymorphisms in such data remain poorly exploited. Currently, allele-specific expression (ASE) studies focus almost exclusively on genetic variants explaining expression differences (cis-eQTLs), largely ignoring other ASE effects. The latter are typically associated with higher variance in expression of both copies of a gene, here called Allelic Divergence (AD). We therefore developed an RNAseq-driven population-level beta-binomial mixture model for (differential) AD detection. The model simultaneously enables RNAseq-driven genotyping, which outperforms alternative RNA genotyping methods when applied on healthy kidney data from The Cancer Genome Atlas. Moreover, we identify well-known non-cis-eQTL ASE, e.g. random monoallelic expression of HLA and immunoglobulin genes in healthy kidney, as well as allele-specific aberrations in clear cell kidney carcinoma, including long-range epigenetic silencing of protocadherins, copy-number alterations, and loss of imprinting. These methods are available as the Modeller of Allelic Gene Expression (MAGE) tool suite: https://biobix.github.io/MAGE/.

bioinformatics↗