Biology subjects

Wayland, M. T.

Publications and source records attributed to Wayland, M. T..

3 recordsLinked to original sources

bioRxiv2021

The arrested state of processing bodies supports mRNA regulation in early development

Biomolecular condensates that form via liquid-liquid phase separation can exhibit diverse physical states. Despite considerable progress, the relevance of condensate physical states for in vivo biological function remains limited. Here, we investigated the physical properties of in vivo processing bodies (P bodies) and their impact on mRNA storage in mature Drosophila oocytes. We show that the conserved DEAD-box RNA helicase Me31B forms P body condensates which adopt a less dynamic, arrested physical state. We demonstrate that structurally distinct proteins and hydrophobic and electrostatic interactions, together with RNA and intrinsically disordered regions, regulate the physical properties of P bodies. Finally, using live imaging, we show that the arrested state of P bodies is required to prevent the premature release of bicoid (bcd) mRNA, a body axis determinant, and that P body dissolution leads to bcd release. Together, this work establishes a role for arrested states of biomolecular condensates in regulating cellular function in a developing organism.

cell biology↗

bioRxiv2020

Rapid speciation of cichlids fishes may be explained by evolutionary divergence of novel open reading frames

Novel open reading frames (nORFs) with coding potential may arise from noncoding DNA. Not much is known about their emergence, functional role, fixation in a population or contribution to adaptive radiation. Cichlids fishes exhibit extensive phenotypic diversification and speciation. Encounters with new environments alone are not sufficient to explain this striking diversity of cichlid radiation because other taxa coexistent with the Cichlidae demonstrate lower species richness. Wagner et al analyzed cichlid diversification in 46 African lakes and reported that both extrinsic environmental factors and intrinsic lineage-specific traits related to sexual selection have strongly influenced the cichlid radiation 1, which indicates the existence of unknown molecular mechanisms responsible for rapid phenotypic diversification, such as emergence of novel open reading frames (nORFs). In this study, we integrated transcriptomic and proteomic signatures from two tissues of two cichlids species, identified nORFs and performed evolutionary analysis on these nORF regions. Our results suggest that the time scale of speciation of the two species and evolutionary divergence of these nORF genomic regions are similar and indicate a potential role for these nORFs in speciation of the cichlid fishes.

evolutionary biology↗

bioRxiv2017

Identification And Prioritisation Of Variants In The Short Open-Reading Frame Regions Of The Human Genome

As whole-genome sequencing technologies improve and accurate maps of the entire genome are assembled, short open-reading frames (sORFs) are garnering interest as functionally important regions that were previously overlooked. However, there is a paucity of tools available to investigate variants in sORF regions of the genome. Here we investigate the performance of commonly used tools for variant calling and variant prioritisation in these regions, and present a framework for optimising these processes. First, the performance of four widely used germline variant calling algorithms is systematically compared. Haplotype Caller is found to perform best across the whole genome, but FreeBayes is shown to produce the most accurate variant set in sORF regions. An accurate set of variants is found by taking the intersection of called variants. The potential deleteriousness of each variant is then predicted using a pathogenicity scoring algorithm developed here, called sORF-c. This algorithm uses supervised machine-learning to predict the pathogenicity of each variant, based on a holistic range of functional, conservation-based and region-based scores defined for each variant. By training on a dataset of over 130,000 variants, sORF-c outperforms other comparable pathogenicity scoring algorithms on a test set of variants in sORF regions of the human genome.\n\nList of Abbreviations

genetics↗