Biology subjects

Sena, F.

Publications and source records attributed to Sena, F..

3 recordsLinked to original sources

bioRxiv2026

Scalable computation of ultrabubbles in pangenomes by orienting bidirected graphs

MotivationPangenome graphs are increasingly used in bioinformatics, ranging from environmental surveillance and crop improvement to the construction of population-scale human pangenomes. As these graphs grow in size, methods that scale efficiently become essential. A central task in pangenome analysis is the discovery of variation structures. In directed graphs, the most widely studied such structures, superbubbles, can be identified in linear time. Their canonical generalization to bidirected graphs, ultrabubbles, more accurately models DNA reverse complementarity. However, existing ultrabubble algorithms are quadratic in the worst case. ResultsWe show that all ultrabubbles in a bidirected graph containing at least one tip or one cutvertex--a common property of pangenome graphs--can be computed in linear time. Our key contribution is a new linear-time orientation algorithm that transforms such a bidirected graph into a directed graph of the same size, in practice. Orientation conflicts are resolved by introducing auxiliary source or sink vertices. We prove that ultrabubbles in the original bidirected graph correspond to weak superbubbles in the resulting directed graph, enabling the use of existing lineartime algorithms. Our approach achieves speedups of up to 25xover the ultrabubble implementation in vg, and of more than 200x over BubbleGun, enabling scalable pangenome analyses. For example, on the v2.0 pangenome graph constructed by the Human Pangenome Reference Consortium from 232 individuals, after reading the input, our method completes in under 3 minutes, while vg requires more than one hour, and four times more RAM. AvailabilityOur method is implemented in the BubbleFinder tool github.com/algbio/BubbleFinder, via the new ultrabubbles subcommand. Contactalexandru.tomescu@helsinki.fi

bioinformatics↗

bioRxiv2025

Liquid-phase determination of Arabidopsis respiration and photosynthesis using Clark-type O2 electrodes

Photosynthesis and respiration are fundamental metabolic processes in plants, tightly connected through shared substrates, energy dynamics, and redox balance. Arabidopsis is the key genetic model for plants but monitoring these sorts of physiological processes presents significant challenges using traditional gas-exchange or fluorescence-based techniques due to the small size of intact Arabidopsis thaliana (arabidopsis) seedlings. Here, we validate and characterize the use of Clark-type oxygen electrodes, specifically the Hansatech Oxytherm+P system, to quantify both photosynthetic and respiratory activity in intact arabidopsis seedlings. By monitoring oxygen evolution in dark and light phases, we demonstrate that oxygen consumption and production correspond to mitochondrial respiration and photosynthesis, respectively. These processes were modulated by tissue biomass, light intensity, developmental stage, and stress conditions. Specific inhibitors such as potassium cyanide and paraquat confirmed that the recorded changes in oxygen concentrations reflected mitochondrial cytochrome oxidase activity and photosystem electron transport-dependent oxygen production, respectively. Moreover, oxygen evolution increased significantly with bicarbonate supplementation, validating the systems sensitivity to carbon fixation. We further showed that photosynthetic activity measured with this method correlates with a quantitative green index and responds dynamically to de-etiolation, abiotic stress (salt, osmotic, oxidative), and temperature shifts. Our study lays the groundwork for measuring photosynthesis based on oxygen evolution and respiration in arabidopsis knockout mutants, CRISPR lines, overexpression lines and ecotypes using Clark-type oxygen electrodes and highlights key considerations and limitations to consider when applying this approach. This platform could also be adapted for many other small tissue plant samples.

plant biology↗

bioRxiv2023

Flowtigs: safety in flow decompositions for assembly graphs

A decomposition of a network flow is a set of weighted paths whose superposition equals the flow. The problem of characterising and computing safe walks for flow decompositions has so far seen only a partial solution by restricting the flow decomposition to consist of paths, and the graph to be directed and acyclic (DAG). However, the problem of decomposing into closed walks in a general graph (allowing cycles) is still open. In this paper, we give a simple and linear-time-verifiable complete characterisation (flowtigs) of walks that are safe in such general flow decompositions, i.e. that are subwalks of any possible flow decomposition. Our characterisation generalises over the previous one for DAGs, using a more involved proof of correctness that works around various issues introduced by cycles. We additionally provide an optimal O(mn)-time algorithm that identifies all maximal flowtigs and represents them inside a compact structure. We also implement this algorithm and show that it is very fast in practice. On the practical side, we study flowtigs in the use-case of metagenomic assembly. By using the species abundances as flow values of the metagenomic assembly graph, we can model the possible assembly solutions as flow decompositions into weighted closed walks. Compared to reporting unitigs or maximal safe walks based only on the graph structure (structural contigs), reporting flowtigs results in a notably more contiguous assembly. Specifically, on shorter contigs (75-percentile), we get an improvement in assembly contiguity of up to 99% over unitigs, and on the 50-percentile of contiguity we get an improvement of up to 17% over unitigs. These improvements that flowtigs bring over unitigs are 4-14x larger that what structural contigs bring over unitigs.

bioinformatics↗