Biology subjects

Glover, N.

Publications and source records attributed to Glover, N..

11 recordsLinked to original sources

bioRxiv2025

Incomplete functional divergence drives genetic synergy during floral development in tomato

Genetic synergy arises from interactions between functionally related genes that control complex traits in plants and animals. Synergy occurs when the combined effect of multiple genes exceeds the additive contribution from each individual gene. However, genetic mechanisms that drive and maintain synergy remain largely elusive. Here, we investigated synergistic interactions among SEPALLATA MADS-box genes during floral development in tomato. We discovered that synergy emerges from duplicated genes that partitioned functions to regulate inflorescence architecture and floral organ identity. Moreover, synergistic interactions are reflected in non-additive expression changes that coordinate successive developmental stages. Finally, we demonstrate that synergy occurs due to residual redundancy on a dose-sensitive module guiding floral identity. These results indicate that synergy emerges as a relic of redundancy when functional divergence remains incomplete due to gene dosage constraints. Our work provides insights into mechanisms through which gene families diverge to produce the substrate for biological innovations during evolution.

genetics↗

bioRxiv2024

Unveiling the Functional Fate of Duplicated Genes Through Expression Profiling and Structural Analysis

Gene duplication is a major evolutionary source of functional innovation. Following duplication events, gene copies (paralogues) may undergo various fates, including retention with functional modifications (such as sub-functionalisation or neo-functionalisation) or loss. When paralogues are retained, this results in complex orthology relationships, including one-to-many or many-to-many. In such cases, determining which one-to-one pair is more likely to have conserved functions can be challenging. It has been proposed that, following gene duplication, the copy that diverges more slowly in sequence is more likely to maintain the ancestral function --referred to here as "the least diverged orthologue (LDO) conjecture". This study explores this conjecture, using a novel method to identify asymmetric evolution of paralogues and apply it to all gene families across the Tree of Life in the PANTHER database. Structural data for over 1 million proteins and expression data for 16 animals and 20 plants were then used to investigate functional divergence following duplication. This analysis, the most comprehensive to date, revealed that whilst the majority of paralogues display similar rates of sequence evolution, significant differences in branch lengths following gene duplication can be correlated with functional divergence. Overall, the results support the least diverged orthologue conjecture, suggesting that the least diverged orthologue (LDO) tends to retain the ancestral function, whilst the most diverged orthologue (MDO) may acquire a new, potentially specialised, role.

evolutionary biology↗

bioRxiv2024

EdgeHOG: fine-grained ancestral gene order inference at tree-of-life scale

Ancestral genomes are essential for studying the diversification of life from the last universal common ancestor to modern organisms. Methods have been proposed to infer ancestral gene order, but they lack scalability, limiting the depth to which gene neighborhood evolution can be traced back. We introduce edgeHOG, a tool designed for accurate ancestral gene order inference with linear time complexity. Validated on various benchmarks, edgeHOG was applied to the entire OMA orthology database, encompassing 2,845 extant genomes across all domains of life. This represents the first tree-of-life scale inference, resulting in 1,133 ancestral genomes. In particular, we reconstructed ancestral contigs for the last common ancestor of eukaryotes, dating back around 1.8 billion years, and observed significant functional association among neighboring genes. The method also dates gene adjacencies, revealing conserved histone clusters and rapid sex chromosome rearrangements, enabling computational inference of these features.

evolutionary biology↗

bioRxiv2024

Orthology inference at scale with FastOMA

The surge in genome data, with ongoing efforts aiming to sequence 1.5M eukaryotes in a decade, could revolutionise genomics, revealing the origins, evolution, and genetic innovations of biological processes. Yet, traditional genomics methods scale poorly with such large datasets. Addressing this, "FastOMA" provides linear scalability, enabling the processing of thousands of eukaryotic genomes within a day. FastOMA maintains the high accuracy and resolution of the well-established OMA approach in benchmarks. FastOMA is available at https://github.com/DessimozLab/FastOMA/.

bioinformatics↗

bioRxiv2024

Repairing a deleterious domestication variant in a floral regulator of tomato by base editing

Crop genomes accumulated deleterious mutations, a symptom known as the cost of domestication. Precision genome editing has been proposed to eliminate such potentially harmful mutations, however, experimental demonstration is lacking. Here, we identified a deleterious mutation in the tomato transcription factor SUPPRESSOR OF SP2 (SSP2), which became prevalent in the domesticated germplasm and diminished DNA-binding to genome-wide targets. We found that SSP2 acts partially redundant with its paralog SSP to regulate shoot and inflorescence architecture. However, redundancy was compromised during tomato domestication and completely lost in the closely-related species Physalis grisea, in which a single ortholog regulates shoot branching. We applied base editing to directly repair the deleterious mutation in cultivated tomato and obtained plants with compact growth that provide an early fruit yield. Our work shows how deleterious variants sensitized modern genotypes for phenotypic tuning and illustrates how repairing deleterious mutations with genome editing may allow predictable crop improvement.

genetics↗

bioRxiv2022

Multifaceted quality assessment of gene repertoire annotation with OMArk

Assessing the quality of protein-coding gene repertoires is critical in an era of increasingly abundant genome sequences for a diversity of species. State-of-the-art genome annotation assessment tools measure the completeness of a gene repertoire, but are blind to other types of errors, such as gene over-prediction or contamination. We developed OMArk, a software relying on fast, alignment-free sequence comparisons between a query proteome and precomputed gene families across the tree of life. OMArk assesses not only the completeness, but also the consistency of the gene repertoire as a whole relative to closely related species. It also reports likely contamination events. We validated OMArk with simulated data, then performed an analysis of the 1805 UniProt Eukaryotic Reference Proteomes, illustrating its usefulness for comparing and prioritizing proteomes based on their quality measures. In particular, we found strong evidence of contamination in 59 proteomes, and identified error propagation in avian gene annotation resulting from the use of a fragmented zebra finch proteome as reference. OMArk is available on GitHub (https://github.com/DessimozLab/OMArk), as a Python package on PyPi, and as an interactive online tool at https://omark.omabrowser.org/.

bioinformatics↗

bioRxiv2022

Control of PHYTOCHROME KINASE SUBSTRATE subcellular localization and biological activity by protein S-acylation

PHYTOCHROME KINASE SUBSTRATE (PKS) proteins are involved in light-regulated growth orientation responses. They act downstream of phytochromes to control hypocotyl gravitropism in the light and act early in phototropin signaling. Despite their importance for plant development, little is known about their molecular mode of action except that they belong to a protein complex comprising the phototropins at the plasma membrane. Identifying evolutionarily conservation is one approach to reveal biologically important protein motifs. Here, we show that PKS sequences are restricted to seed plants and that these proteins share 6 motifs (A to F from the N- to the C-terminus). While motif D is also found in BIG GRAIN proteins the remining domains are PKS specific. We provide evidence that motif C is S-acylated on highly conserved cysteines, which mediates PKS protein association with the plasma membrane. This motif is also required for PKS4-mediated phototropism and control of hypocotyl gravitropism in the light. Finally, our data suggests that the mode of PKS4 plasma membrane association is important for its biological activity. Our work identifies the mode of plasma membrane association of PKS proteins and strongly suggests that this is their site of action to modulate environmentally regulated organ positioning.

plant biology↗

bioRxiv2021

Protein length distribution is remarkably consistent across Life

In every living species, the function of a protein depends on its organisation of structural domains, and the length of a protein is a direct reflection of this. Because every species evolved under different evolutionary pressures, the protein length distribution, much like other genomic features, is expected to vary across species. Here we evaluated this diversity by comparing protein length distribution across 2,326 species (1,688 bacteria, 153 archaea and 485 eukaryotes). We found that proteins tend to be on average slightly longer in eukaryotes than in bacteria or archaea, but that the variation of length distribution across species is low, especially compared to the variation of other genomic features (genome size, number of proteins, gene length, GC content, isoelectric points of proteins). Moreover, most cases of atypical protein length distribution appear to be due to artifactual gene annotation, suggesting the actual variation of protein length distribution across species is even smaller. These results open the way for developing a genome annotation quality metric based on protein length distribution to complement conventional quality measures. Overall, our findings show that protein length distribution between living species is more consistent than previously thought, and provide evidence for a universal purifying selection on protein length, whose mechanism and fitness effect remain intriguing open questions.

evolutionary biology↗

bioRxiv2019

Acetobacteraceae in the honey bee gut comprise two distant clades with diverging metabolism and ecological niches

Various bacteria of the family Acetobacteraceae are associated with the gut environment of insects. Honey bees harbor two distinct Acetobacteraceae in their gut, Alpha2.1 and Alpha2.2. While Alpha2.1 seems to be a gut specialist, Alpha2.2 is also found in the diet (e.g. royal jelly), the hypopharyngeal glands, and the larvae of honey bees. Here, we combined amplicon and genome sequencing to better understand functional differences associated with the ecology of Alpha2.1 and Alpha2.2. We find that the two phylotypes are differentially distributed along the worker and queen bee gut. Phylogenetic analysis shows that Alpha2.2 is nested within the acetic acid bacteria and consists of two separate sub-lineages, whereas Alpha2.1 belongs to a basal lineage with an unusual GC content for Acetobacteraceae. Gene content analysis revealed major differences in the central carbon and respiratory metabolism between the two phylotypes. While Alpha2.2 encodes two periplasmic dehydrogenases to carry out oxidative fermentation, Alpha2.1 lacks this capability, but instead harbors a diverse set of cytoplasmic dehydrogenases. These differences are accompanied by the loss of the TCA cycle in Alpha2.2, but not in Alpha2.1. We speculate that Alpha2.2 has specialized for fast-resource utilization through incomplete carbohydrate oxidation, giving it an advantage in sugar-rich environments such as royal jelly. On the contrary, the broader metabolic range of Alpha2.1 may provide an advantage in the worker bee hindgut, where competition with other bacteria and flexibility in resource utilization may be relevant for persistence. Our results show that bacteria belonging to the same family may utilize vastly different strategies to colonize niches associated with the animal gut.

genomics↗

bioRxiv2018

Genomic changes underlying host specialization in the bee gut symbiont Lactobacillus Firm5

Bacteria that engage in longstanding associations with particular hosts are expected to evolve host-specific adaptations that limit their capacity to thrive in other environments. Consistent with this, many gut symbionts seem to have a limited host range, based on community profiling and phylogenomics. However, few studies have experimentally investigated host specialization of gut symbionts and underlying mechanisms have largely remained elusive. Here, we studied host specialization of a dominant gut symbiont of social bees, Lactobacillus Firm5. We show that Firm5 strains isolated from honey bees and bumble bees separate into deep-branching phylogenetic lineages. Despite their divergent evolution, colonization experiments show that bumble bee strains are capable of colonizing the honey bee gut. However, they were less successful than honey bee strains, and competition with honey bee strains completely abolished their colonization, whereas honey bee strains were able to coexist. This suggests that both host selection and interbacterial competition play important roles for host specialization. Using comparative genomics of 27 Firm5 isolates, we identified candidate genomic changes underlying host specialization. We found that honey bee strains harbored a larger and more diverse gene pool of carbohydrate-related functions than bumble bee strains. As dietary-derived carbohydrates are the main energy source for strains of the Firm5 phylotype, the metabolic flexibility of honey bee strains may give these bacteria a competitive advantage over bumble bee strains in colonizing the gut niche and hence contribute to host specialization.

microbiology↗

bioRxiv2018

OMA standalone: orthology inference among public and custom genomes and transcriptomes

Genomes and transcriptomes are now typically sequenced by individual labs, but analysing them often remains challenging. One essential step in many analyses lies in identifying orthologs--corresponding genes across multiple species--but this is far from trivial. The OMA (Orthologous MAtrix) database is a leading resource for identifying orthologs among publicly available, complete genomes. Here, we describe the OMA pipeline available as a standalone program for Linux and Mac. When run on a cluster, it has native support for the LSF, SGE, PBS Pro, and Slurm job schedulers and can scale up to thousands of parallel processes. Another key feature of OMA standalone is that users can combine their own data with existing public data by exporting genomes and pre-computed alignments from the OMA database, which currently contains over 2100 complete genomes. We compare OMA standalone to other methods in the context of phylogenetic tree inference, by inferring a phylogeny of the Lophotrochozoa, a challenging clade within the Protostomes. We also discuss other potential applications of OMA standalone, including identifying gene families having undergone duplications/losses in specific clades, and identifying potential drug targets in non-model organisms. OMA Standalone is available at http://omabrowser.org/standalone under the permissible open source Mozilla Public License Version 2.0.

bioinformatics↗