Biology subjects

Zavolan, M.

Publications and source records attributed to Zavolan, M..

26 records · Page 2Linked to original sources

bioRxiv2021

Shortening of 3' UTRs in most cell types composing tumor tissues implicates alternative polyadenylation in protein metabolism

During pre-mRNA maturation 3 end processing can occur at different polyadenylation sites in the 3 untranslated region (3 UTR) to give rise to transcript isoforms that differ in the length of their 3UTRs. Longer 3 UTRs contain additional cis-regulatory elements that impact the fate of the transcript and/or of the resulting protein. Extensive alternative polyadenylation (APA) has been observed in cancers, but the mechanisms and roles remain elusive. In particular, it is unclear whether the APA occurs in the malignant cells or in other cell types that infiltrate the tumor. To resolve this, we developed a computational method, called SCUREL, that quantifies changes in 3UTR length between groups of cells, including cells of the same type originating from tumor and control tissue. We used this method to study APA in human lung adenocarcinoma (LUAD). SCUREL relies solely on annotated 3UTRs and on control systems, such as T cell activation and spermatogenesis gives qualitatively similar results at much greater sensitivity compared to the previously published scAPA method. In the LUAD samples, we find a general trend towards 3UTR shortening not only in cancer cells compared to the cell type of origin, but also when comparing other cell types from the tumor vs. the control tissue environment. However, we also find high variability in the individual targets between patients. The findings help to understand the extent and impact of APA in LUAD, which may support improvements in diagnosis and treatment.

bioinformatics↗

bioRxiv2021

Distinct and additive effects of calorie restriction and rapamycin in aging skeletal muscle

As global life expectancy continues to climb, maintaining skeletal muscle function is increasingly essential to ensure a good life quality for aging populations. Calorie restriction (CR) is the most potent and reproducible intervention to extend health and lifespan, but is largely unachievable in humans. Therefore, identification of "CR mimetics" has received much attention. CR targets nutrient-sensing pathways centering on mTORC1. The mTORC1 inhibitor, rapamycin, has been proposed as a potential CR mimetic and is proven to counteract age-related muscle loss. Therefore, we tested whether rapamycin acts via similar mechanisms as CR to slow muscle aging. Contrary to our expectation, long-term CR and rapamycin-treated geriatric mice display distinct skeletal muscle gene expression profiles despite both conferring benefits to aging skeletal muscle. Furthermore, CR improved muscle integrity in a mouse with nutrient-insensitive sustained muscle mTORC1 activity and rapamycin provided additive benefits to CR in aging mouse muscles. Therefore, RM and CR exert distinct, compounding effects in aging skeletal muscle, opening the possibility of parallel interventions to counteract muscle aging.

physiology↗

bioRxiv2021

Nanopore sequencing reveals endogenous NMD-targeted isoforms in human cells

BackgroundNonsense-mediated mRNA decay (NMD) is a eukaryotic, translation-dependent degradation pathway that targets mRNAs with premature termination codons and also regulates the expression of some mRNAs that encode full-length proteins. Although many genes express NMD-sensitive transcripts, identifying them based on short-read sequencing data remains a challenge. ResultsTo identify and analyze endogenous targets of NMD, we applied cDNA Nanopore sequencing and short-read sequencing to human cells with varying expression levels of NMD factors. Our approach detects full-length NMD substrates that are highly unstable and increase in levels or even only appear when NMD is inhibited. Among the many new NMD-targeted isoforms that our analysis identified, most derive from alternative exon usage. The isoform-aware analysis revealed many genes with significant changes in splicing but no significant changes in overall expression levels upon NMD knockdown. NMD-sensitive mRNAs have more exons in the 3'UTR and, for those mRNAs with a termination codon in the last exon, the length of the 3'UTR per se does not correlate with NMD sensitivity. Analysis of splicing signals reveals isoforms where NMD has been co-opted in the regulation of gene expression, though the main function of NMD seems to be ridding the transcriptome of isoforms resulting from spurious splicing events. ConclusionsLong-read sequencing enabled the identification of many novel NMD-sensitive mRNAs and revealed both known and unexpected features concerning their biogenesis and their biological role. Our data provide a highly valuable resource of human NMD transcript targets for future genomic and transcriptomic applications.

molecular biology↗

bioRxiv2020

The transcriptional landscape of a hepatoma cell line grown on scaffolds of extracellular matrix proteins

The behavior of cells in vivo is complex and highly dynamic, as it results from an interplay between components of the intercellular matrix proteins with surface receptor and other microenvironmental cues. Although the effects of the cellular niche have been investigated for a number of cell types using different molecular approaches, comprehensive assessments of how the global transcriptome responds to 3D scaffolds composed of various extracellular matrix (ECM) constituents are still lacking. In this study, we explored the effect of the biomechanical parameters of Collagen I and Matrigel (ECM) on transcriptional gene regulation in a cell culture system. Using Huh-7 cells cultured on traditional cell culture plates or on the components of the ECM at different concentrations to modulate microenvironment properties, we have generated transcriptome sequencing data that may be further explored to understand the differentiation and growth potential of this cell for the development of 3D cultures. Assessment of the hepatocyte phenotype in relation to our transcriptomic data set would be very useful for the development of systems mimicking the in vivo structure and function of liver cells which still remains a challenge.

systems biology↗

bioRxiv2019

Bayesian inference of the gene expression states of single cells from scRNA-seq data

In spite of a large investment in the development of methodologies for analysis of single-cell RNA-seq data, there is still little agreement on how to best normalize such data, i.e. how to quantify gene expression states of single cells from such data. Starting from a few basic requirements such as that inferred expression states should correct for both intrinsic biological fluctuations and measurement noise, and that changes in expression state should be measured in terms of fold-changes rather than changes in absolute levels, we here derive a unique Bayesian procedure for normalizing single-cell RNA-seq data from first principles. Our implementation of this normalization procedure, called Sanity (SAmpling Noise corrected Inference of Transcription activitY), estimates log expression values and associated errors bars directly from raw UMI counts without any tunable parameters. Comparison of Sanity with other recent normalization methods on a selection of scRNA-seq datasets shows that Sanity outperforms other methods on basic downstream processing tasks such as clustering cells into subtypes and identification of differentially expressed genes. More importantly, we show that all other normalization methods present severely distorted pictures of the data. By failing to account for biological and technical Poisson noise, many methods systematically predict the lowest expressed genes to be most variable in expression, whereas in reality these genes provide least evidence of true biological variability. In addition, by confounding noise removal with lower-dimensional representation of the data, many methods introduce strong spurious correlations of expression levels with the total UMI count of each cell as well as spurious co-expression of genes.

bioinformatics↗

bioRxiv2019

AGO1x prevents dsRNA-induced interferon signaling to promote breast cancer cell proliferation

Initially reported for viral RNA, elongation of polypeptide chains beyond the stop codon (translational readthrough (TR)) also occurs on eukaryotic transcripts. TR diversifies the proteome and can modulate protein levels 1-6. Here we report that AGO1x, a conserved TR isoform of Argonaute 1, is generated in highly proliferative breast cancer cells, where it curbs accumulation of double stranded RNAs, the induction of the interferon response and apoptosis. In contrast to other mammalian Argonaute protein family members with primarily cytoplasmic functions, AGO1x localizes to the nucleus, in the vicinity of nucleoli. We identify a novel interaction of AGO1x with the Polyribonucleotide Nucleotidyltransferase 1, depletion of either protein leading to dsRNA accumulation and impaired cell proliferation. Our study thus uncovers a novel function of an Argonaute protein outside of the miRNA effector pathway, in buffering dsRNA-induced interferon responses. As AGO1x expression is tightly linked to breast cancer cell proliferation, our study suggests a new direction for limiting tumor growth.

cell biology↗

bioRxiv2018

Protein synthesis rates and ribosome occupancies reveal determinants of translation elongation rates

Although protein synthesis dynamics has been studied both with theoretical models and by profiling ribosome footprints, the determinants of ribosome flux along open reading frames (ORFs) are not fully understood. Combining measurements of protein synthesis rate with ribosome footprinting data, we here inferred translation initiation and elongation rates for over a thousand ORFs in exponentially-growing wildtype yeast cells. We found that the amino acid composition of synthesized proteins is as important a determinant of translation elongation rate as parameters related to codon and tRNA adaptation. We did not find evidence of ribosome collisions curbing the protein output of yeast transcripts, either in high translation conditions associated with exponential growth, or in strains in which deletion of individual ribosomal protein genes leads to globally increased or decreased translation. Slow translation elongation is characteristic of RP-encoding transcripts, which have markedly lower protein output than other transcripts with equally high ribosome densities.\n\nSignificance StatementAlthough sequencing of ribosome footprints has uncovered new aspects of mRNA translation, the determinants of ribosome flux remain incompletely understood. Combining ribosome footprint data with measurements of protein synthesis rates, we here inferred translation initiation and elongation rates for over a thousand ORFs in yeast strains with varying translation capacity. We found that the translation elongation rate varies up to ~20-fold among yeast transcripts, and is significantly correlated with the rate of translation initiation. Furthermore, the amino acid composition of synthesized proteins impacts the rate of translation elongation to the same extent as measures of codon and tRNA adaptation. Transcripts encoding ribosomal proteins are translated especially slow, having markedly lower protein output than other transcripts with equally high ribosome densities.

biophysics↗

bioRxiv2017

Discovery of global regulators of 3’ untranslated region processing in cancers with KAPAC

3 UTR length is regulated in relation to cellular state. To uncover key regulators of poly(A) site (PAS) use in specific conditions, we have developed PAQR, a method for quantifying PAS use from RNA sequencing data and KAPAC, an approach that infers activities of oligomeric sequence motifs on PAS choice. Application of PAQR and KAPAC to RNA sequencing data from normal and tumor tissue samples uncovered sequence motifs that can explain changes in cleavage and polyadenylation in specific cancers. In particular, our analysis points to Polypyrimidine tract binding protein 1 as a regulator of PAS choice in glioblastoma.

systems biology↗