Biology subjects

Van Damme, R.

Publications and source records attributed to Van Damme, R..

4 recordsLinked to original sources

bioRxiv2026

Elevated genetic load is associated with reduced bite force in insular lizard populations

Demographic history can profoundly shape genomic variation by altering levels of inbreeding, the strength of genetic drift, and the efficacy of purifying selection, thereby influencing both the accumulation and expression of deleterious variation. Yet the extent to which these genomic consequences translate into organismal performance remains poorly understood. Here, we investigated how contrasting demographic histories shape genomic diversity, inbreeding, genetic load, and performance across mainland and insular populations of the Italian wall lizard, Podarcis siculus. Using whole-genome sequence data from 263 wild-caught individuals and field-based performance measurements from 134 lizards, we characterised population structure and demographic history, quantified genomic diversity, runs of homozygosity, and deleterious variation, and tested associations between genomic inbreeding and performance traits. Island populations showed reduced genetic diversity, increased autozygosity, and elevated genetic load relative to mainland populations, consistent with stronger genetic drift and reduced efficacy of purifying selection. Patterns of deleterious variation were consistent with purging of strongly, but not mildly, deleterious variants. Greater genomic autozygosity was associated with reduced bite force in island lizards, a pattern consistent with inbreeding depression, whereas sprint speed, sperm quality, immunocompetence, and spatial cognition showed no significant association with inbreeding. Genome-wide mapping of runs of homozygosity further identified multiple genomic regions associated with reduced bite performance. Together, these results show how demographic history shapes genomic diversity, homozygosity, and deleterious variation in wild vertebrate populations, while revealing that phenotypic consequences can be trait-specific, a pattern that may reflect differences in genetic architecture and the extent of environmental influence on trait variation.

evolutionary biology↗

bioRxiv2023

snoRNA-guided tRNA 2'-O-methylation controls codon-biased gene expression and cellular states

snoRNAs are a large family of noncoding (nc)RNAs present across eukaryotes and archaea. While a subset of them guide 2-O- methylation (Nm) and pseudouridylation ({Psi}) of rRNAs and snRNAs, targets of most snoRNAs remain unknown. Here we used PARIS2 to map snoRNA targets, revealing an extensive and conserved snoRNA-tRNA interaction network. Using optimized denatured RiboMeth-seq (dRMS), we discovered snoRNA-guided Nm sites in ncRNAs, including tRNAs. Loss of snoRNAs and their associated 2-O-methyltransferase FBL reduced tRNA modifications and increased fragmentation. CRISPR knockout of the D97/D133 family of snoRNAs reduced the activity and levels of several target tRNAs, including elongator (e)Met-CAU, leading to codon-biased transcriptome and translatome in human cells. The codon-biased gene expression tipped the balance between the dichotomous cellular states of proliferation and differentiation, and skewed germ layer potential of mouse embryonic stem cells. Together, we discovered a snoRNA-guided tRNA modification mechanism controlling codon-biased gene expression and cellular states.

biochemistry↗

bioRxiv2021

Chemical Reversible Crosslinking Enables Measurement of RNA 3D Distances and Alternative Conformations in Cells

Three-dimensional (3D) structures dictate the functions of RNA molecules in a wide variety of biological processes. However, direct determination of RNA 3D structures in vivo is difficult due to their large sizes, conformational heterogeneity, and dynamics. Here we present a new method, Spatial 2-Hydroxyl Acylation Reversible Crosslinking (SHARC), which uses chemical crosslinkers of defined lengths to measure distances between nucleotides in cellular RNA. Integrating crosslinking, exonuclease (exo) trimming, proximity ligation, and high throughput sequencing, SHARC enables transcriptome-wide tertiary structure contact maps at high accuracy and precision, revealing heterogeneous RNA structures and interactions. SHARC data provide constraints that improves Rosetta-based RNA 3D structure modeling at near-nanometer resolution. Integrating SHARC-exo with other crosslinking-based methods, we discover compact folding of the 7SK RNA, a critical regulator of transcriptional elongation. These results establish a new strategy for measuring RNA 3D distances and alternative conformations in their native cellular context.

biochemistry↗

bioRxiv2020

Metagenomics workflow for hybrid assembly, differential coverage binning, transcriptomics and pathway analysis (MUFFIN)

Metagenomics has redefined many areas of microbiology. However, metagenome-assembled genomes (MAGs) are often fragmented, primarily when sequencing was performed with short reads. Recent long-read sequencing technologies promise to improve genome reconstruction. However, the integration of two different sequencing modalities makes downstream analyses complex. We, therefore, developed MUFFIN, a complete metagenomic workflow that uses short and long reads to produce high-quality bins and their annotations. The workflow is written by using Nextflow, a workflow orchestration software, to achieve high reproducibility and fast and straightforward use. This workflow also produces the taxonomic classification and KEGG pathways of the bins and can be further used by providing RNA-Seq data (optionally) for quantification and annotation. We tested the workflow using twenty biogas reactor samples and assessed the capacity of MUFFIN to process and output relevant files needed to analyze the microbial community and their function. MUFFIN produces functional pathway predictions and if provided de novo transcript annotations across the metagenomic sample and for each bin. Author SummaryRVD did the development and design of MUFFIN and wrote the first draft; BM and EBR did the critical reading and correction of the manuscript; MH did the critical reading of the manuscript and the general adjustments for the metagenomic workflow; AV did the critical reading of the manuscript and adjustments for the taxonomic classifications. CB supervised the project, did the workflow design, helped with the implementation, and revised the manuscript.

bioinformatics↗