Biology subjects

Ioannou, A.

Publications and source records attributed to Ioannou, A..

3 recordsLinked to original sources

bioRxiv2026

Benchmarking tissue- and cell type-of-origin deconvolution in cell-free transcriptomics

Plasma cell-free RNA (cfRNA) reflects tissue- and cell-type-specific activity across pathological states and is a promising biomarker for organ injury and disease. Computational deconvolution methods are widely used to infer organ and cell-type contributions to cfRNA profiles. However, most were originally developed for single-tissue bulk transcriptomes and their performance in body-wide cfRNA settings, where any tissue or cell type can contribute, remains poorly characterised. Here, we present a systematic benchmarking of tissue- and cell type-of-origin deconvolution for plasma cfRNA that considers both methodological and reference-related sources of variability under realistic cfRNA simulation settings. We evaluated seven commonly used deconvolution methods across distinct algorithmic classes and multi-organ reference configurations derived from bulk and single-cell atlases. We assessed performance using simulation frameworks that model multi-organ mixtures, technical noise, and transcript degradation. We further examined deconvolution methods across multiple previously published clinical cfRNA cohorts spanning diverse disease contexts. Across both tissue- and cell-type-level analyses, deconvolution performance was strongly influenced by both method choice and reference parameters. Tissue-of-origin inference was comparatively robust across simulated and clinical datasets, recovering disease-associated organ signals and concordance with biochemical markers. In contrast, cell type-of-origin inference showed greater variability and reduced consistency across analytical settings, leading to divergent interpretations in both simulations and published clinical cfRNA cohorts. Together, these findings demonstrate that methodological and reference-related variability are major sources of uncertainty in cfRNA deconvolution, with tissue-level inference being more robust than cell-type-level inference. Our benchmarking framework provides guidance for reference selection and comparative interpretation in cfRNA deconvolution.

bioinformatics↗

bioRxiv2025

Disease-associated genetic variants can cause mutations in tissue-specific protein isoforms

Genetic variants can cause protein-coding mutations that result in disease. Variants are typically interpreted using the reference transcript for a gene. However, most human multi-exon genes encode alternative isoforms. Here, we show that coding exons in alternative isoforms harbour more population variants than exons of reference isoforms, consistent with their reduced evolutionary constraint, and that these variants are more likely to cause nonsynonymous coding mutations. Common and rare disease-associated variants mapping to alternative transcripts can lead to amino acid substitutions predicted to be structurally damaging in the corresponding protein isoform. The alternative transcripts to which disease-associated variants map demonstrate high tissue-specific expression, with many unannotated in reference human genomes, revealed only by long-read RNA-sequencing. As an example, we report an unannotated alternative transcript of the inflammasome regulator DPP9 that is lung epithelium-specific and which harbours a common genetic variant associated with severe COVID-19 and lung fibrosis. The variant causes a p.Leu8Pro missense mutation in an alternative first exon, predicted to disrupt the encoded alpha helix. These findings highlight the importance of considering alternative isoforms, their tissue-specific expression, and full-length transcripts in variant interpretation, with implications for uncovering underappreciated mechanisms of both common and rare disease.

genomics↗

bioRxiv2024

Posttranscriptional tuning of gene expression over a large dynamic range in synthetic tobacco chloroplast operons

Achieving balanced gene expression within synthetic operons requires a spectrum of expression levels. Here we investigate the expression of gfp reporter gene in tobacco chloroplasts, guided by variants of the plastid atpH 5 UTR, which harbors a binding site for PPR10, a protein that activates atpH at the post-transcriptional level. Our findings reveal that endogenous tobacco PPR10 confers distinct levels of reporter activation when coupled with the tobacco and maize atpH 5 UTRs in different design contexts. Notably, high GFP expression was not coupled to stabilization of monocistronic gfp transcripts in dicistronic reporter lines, adding to the evidence that PPR10 activates translation via a mechanism that is independent of its stabilization of monocistronic transcripts. Furthermore, the incorporation of a tRNA upstream of the UTR nearly abolishes gfp mRNA (and GFP protein), resulting in a substantial reduction in GFP accumulation. When combined with a mutant atpH 5 UTR, the tRNA leads to an exceptionally low level of transgene expression. Collectively, this approach allows for tuning reporter gene expression across a wide range, spanning from 0.02% to 25% of the total soluble cellular protein (TSP). These findings highlight the toolbox available for plastid synthetic biology applications requiring multigene expression at varying levels.

bioengineering↗