Biology subjects

Goovaerts, T.

Publications and source records attributed to Goovaerts, T..

3 recordsLinked to original sources

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↗

bioRxiv2019

The RNA Atlas, a single nucleotide resolution map of the human transcriptome

The human transcriptome consists of various RNA biotypes including multiple types of non-coding RNAs (ncRNAs). Current ncRNA compendia remain incomplete partially because they are almost exclusively derived from the interrogation of small- and polyadenylated RNAs. Here, we present a more comprehensive atlas of the human transcriptome that is derived from matching polyA-, total-, and small-RNA profiles of a heterogeneous collection of nearly 300 human tissues and cell lines. We report on thousands of novel RNA species across all major RNA biotypes, including a hitherto poorly-cataloged class of non-polyadenylated single-exon long non-coding RNAs. In addition, we exploit intron abundance estimates from total RNA-sequencing to test and verify functional regulation by novel non-coding RNAs. Our study represents a substantial expansion of the current catalogue of human ncRNAs and their regulatory interactions. All data, analyses, and results are available in the R2 web portal and serve as a basis to further explore RNA biology and function.

genetics↗

bioRxiv2018

A Comprehensive Overview Of Genomic Imprinting In Breast & Its Deregulation In Cancer

Genomic imprinting, the parent-of-origin specific monoallelic expression of genes, plays an important role in growth and development. Loss of imprinting of individual genes has been found in varying cancers, yet data-analytical challenges have impeded systematic studies so far. We developed a mixture distribution model to detect monoallelically expressed loci in a genome-wide manner without the need for genotyping data, and applied the methodology on TCGA breast tissue RNA-seq data. We identified 35 putatively imprinted genes in healthy breast. In breast cancer however, HM13 was featured by significant loss of imprinting and expression upregulation, which could be linked to DNA demethylation. Other imprinted genes (25 out of 35) demonstrated consistent expression downregulation in breast cancer, which often correlated with loss of imprinting. A breast imprinted gene network, deregulated in cancer, might hence be present. In summary, our novel methodology highlights the massive deregulation of imprinting in breast cancer.

cancer biology↗