Biology subjects

Tomkins, M.

Publications and source records attributed to Tomkins, M..

6 recordsLinked to original sources

bioRxiv2025

What is a differentially expressed gene?

The concept of Differentially Expressed Genes (DEGs) is central to RNA-Seq studies, yet their identification suffers from reproducibility issues. This is largely a consequence of the inherent biological and technical variation that cannot be captured with small numbers of replicates. When thresholds for p-values and log2 fold changes are introduced, this variability can propagate an incomplete description of the data, leading to differing interpretations. Here, we compare traditional binary DEG classification with a rank-based method, grounded in Bayesian statistics, using a published yeast dataset comprising over 40 replicates. This analysis reveals how the choice of thresholds and number of replicates results in discrepancies between studies and potentially interesting genes being overlooked. Furthermore, by comparing wild-type with wild-type samples, we show how variability in gene expression can be mistaken for differential expression. Evaluating current practices for navigating the accuracy-error trade-off in the search for differentially expressed genes leads us to advocate rank-based methods and Bayesian statistics to mitigate the limitations of binary classifications and communicate uncertainty.

bioinformatics↗

bioRxiv2025

A Bayesian framework for ranking genes based on their statistical evidence for differential expression

Advances in sequencing technologies have revolutionised our ability to capture the complete RNA profile in tissue samples, allowing for comparative analyses of RNA levels between developmental processes, environmental responses, or treatments. However, quantifying changes in gene expression remains challenging, given inherent biological variability and technological limitations. To address this, we introduce a Bayesian framework for differential gene expression (DGE) analysis. Our framework unifies and streamlines a complex analysis, typically involving parameter estimations and multiple statistical tests, into a concise mathematical equation. This allows statistical evidence for differential expression to be computed rapidly and transparently. We show how this approach can be used to evaluate variabilty of individual genes between replicates. A comparison of our framework with existing tools revealed differences that can be explained by commonly employed thresh-olds in other packages. This motivated us to explore ranking genes based on their statistical evidence as opposed to a binary classification as DEGs. Our analysis leads us to advocate the use of Bayes factors within a rank-based approach. This framework offers enhanced computational efficiency and delivers a transparent way to analyse, interpret and communicate DGE results.

bioinformatics↗

bioRxiv2024

Re-analysis of mobile mRNA datasets highlights challenges in the detection of mobile transcripts from short-read RNA-Seq data

Short-read RNA-Seq analyses of grafted plants have led to the proposal that large numbers of mRNAs move over long distances between plant tissues, acting as potential signals. The detection of transported transcripts by RNA-Seq is both experimentally and computationally challenging, requiring successful grafting, delicate harvesting, rigorous contamination controls and data processing approaches that can identify rare events in inherently noisy data. Here, we perform a meta-analysis of existing datasets and examine the associated bioinformatic pipelines. Our analysis reveals that technological noise, biological variation and incomplete genome assemblies give rise to features in the data that can distort the interpretation. Taking these considerations into account, we find that a substantial number of transcripts that are currently annotated as mobile are left without support from the available RNA-Seq data. Whilst several annotated mobile mRNAs have been validated, we cannot exclude that others may be false positives. The identified issues may also impact other RNA-Seq studies, in particular those using single nucleotide polymorphisms (SNPs) to detect variants.

plant biology↗

bioRxiv2024

Systemic mRNA transport depends on m5C methylation, nuclear mRNA export factors and developmental phase changes

In grafted plants mRNAs can be transported from shoot to root, however, how their mobility is regulated remains poorly understood. Recent work has shown that m5C methylation plays an essential role in systemic mRNA mobility in vegetative plants, but its role at later developmental stages remains unclear. To address this, we examined the mobility of three mobile mRNAs, TCTP1, HSC70.1 and GRP7 in mutants deficient in m5C mRNA methylation. By comparing vegetative and flowering stages, we found that in contrast to GRP7, the reduced mobility of TCTP1 and HSC70.1 observed in the vegetative growth phase is restored upon flowering, indicating that m5C-dependent regulation of RNA transport is developmentally controlled. We further identified two RNA-binding proteins, the nuclear mRNA export factors ALY2 and ALY4, as phloem mobile. ALY2 and ALY4 deficient plants show a similar developmental effect on mRNA mobility as m5C mRNA methylation mutants, suggesting that they contribute to the regulation of systemic mRNA transport. Notably, combined perturbation of m5C methylation and ALY2 or ALY4 results in reduced mRNA mobility even in flowering plants. Together, our findings reveal an unexpected developmental layer of control over mRNA transport and identify the nuclear mRNA export factors ALY2 and ALY4 as potential regulators of long-distance RNA movement. SIGNIFICANCE STATEMENTmRNA m5C methylation is essential for shoot-to-root mRNA transport during plant growth; however, whether and how mRNA mobility is regulated, and whether it changes during development remains unclear. We show that TCTP1 and HSC70.1 mRNA transport is reduced in vegetatively growing m5C-deficient mutants but remains unaffected upon flowering, and identify ALY2 and ALY4 proteins, two nuclear export factors, as additional regulators of long-distance mRNA transport, providing new layer of mRNA transport.

plant biology↗

bioRxiv2022

Non-cell-autonomous HSC70.1 chaperone displays homeostatic feed-back regulation by binding its own mRNA

Heat shock proteins of the HSC70/HSP70 family are evolutionarily conserved chaperones that are involved in protein folding, protein transport and RNA binding. Arabidopsis HSC70 chaperones are thought to act as housekeeping chaperones and as such are involved in many growth-related pathways. Whether Arabidopsis HSC70 binds RNA and its function has remained an open question. Here, we show that the HSC70.1 chaperone binds its own mRNA via its C-terminal Short Variable Region (SVR) and inhibits its own translation. We propose that this negative protein-transcript feedback loop may establish an on-demand chaperone pool that allows for a rapid response to stress. Furthermore, we show that the SVR encoding RNA region is necessary for HSC70.1 transcript mobility to distant tissues and that HSC70.1 transcript and not protein mobility is required to rescue root growth and flowering time of hsc70 mutants. In summary, it seems that the Arabidopsis HSC70.1 chaperone can form a complex with its own transcript to regulate its translation and that both protein and transcript can act in a non-cell-autonomous manner maintaining chaperone homestasis between tissues.

plant biology↗

bioRxiv2021

High expression of VRT2 during wheat spikelet initiation increases the number of rudimentary basal spikelets

Spikelets are the fundamental building blocks of Poaceae inflorescences and their development and branching patterns determine the various inflorescence architectures and grain yield of grasses. In wheat, the central spikelets produce the most and largest grains, while spikelet size gradually decreases acro- and basipetally, giving rise to the characteristic lanceolate shape of wheat spikes. The acropetal gradient correlates with the developmental age of spikelets, however the basal spikelets are developed first and the cause of their small size and rudimentary development is unclear. Here, we adapted G&T-seq, a low-input transcriptomics approach, to characterise gene expression profiles within spatial sections of individual spikes before and after the establishment of the lanceolate shape. We observed larger differences in gene expression profiles between the apical, central and basal sections of a single spike than between any section belonging to consecutive developmental timepoints. We found that SVP MADS-box transcription factors, including VRT-A2, are expressed highest in the basal section of the wheat spike and display the opposite expression gradient to flowering E-class SEP1 genes. Based on multi-year field trials and transgenic lines, we show that higher expression of VRT-A2 in the basal sections of the spike is associated with increased numbers of rudimentary basal spikelets. Our results, supported by computational modelling, suggest that the delayed transition of basal spikelets from vegetative to floral developmental programmes results in the lanceolate shape of wheat spikes. This study highlights the value of spatially resolved transcriptomics to gain new insights into developmental genetics pathways of grass inflorescences. One sentence summaryLarge transcriptional gradients exist within a wheat spike and are associated with rudimentary basal spikelet development, resulting in the characteristic lanceolate shape of wheat spikes.

plant biology↗