Biology subjects

Fuqua, T.

Publications and source records attributed to Fuqua, T..

10 recordsLinked to original sources

bioRxiv2026

Interallelic cis-regulatory dominance promotes robustness and evolutionary innovation

Dominance is a central principle of genetics, yet the mechanistic basis and the evolutionary consequences of dominance arising from cis-regulatory variation remain poorly understood. We examined the evolutionary trajectories of a pleiotropic developmental enhancer in Drosophila. A genotype-phenotype map between D. melanogaster and D. simulans enhancer sequences reveals extensive epistasis, and many homozygous evolutionary paths reduce transcriptional output. In heterozygotes, however, regulatory dominance masks variants that reduce gene expression, potentially relaxing evolutionary constraints. Using allele-specific reporters and imaging, we show that this dominance arises from interallelic interactions (also known as transvection) reinforced by transcriptional hubs. Importantly, this enhancer dominance is cell-type specific, raising the possibility that it conceals deleterious effects in essential tissues while revealing novel, ectopic activity in others. Interallelic regulatory hubs may therefore expand the range of mutational paths available to diploid genomes while preserving essential transcriptional output.

evolutionary biology↗

bioRxiv2025

Strong promoters are mutationally robust

Mutational robustness is the persistence of a phenotype upon mutation. It facilitates molecular evolution and has been characterized in a variety of biological systems, but studies of prokaryotic promoters are limited. Prokaryotic promoters are non-coding DNA sequences that regulate transcription. The main housekeeping promoters ({sigma}70) share two sequence motifs called the -35 and the -10 box that are spaced 17{+/-}1 base pairs (bps) apart. The sequence of these boxes, their distance, and the existence of multiple nearby boxes can determine promoter strength, the ability of a promoter to drive high levels of transcription. Here we used computational modelling to show that the mutational robustness of {sigma}70 promoters - the persistence of promoter strength upon mutation - correlates with promoter strength itself. Mutational robustness is also influenced by potential overlaps between -10 and -35 boxes, and by specific positions within the boxes. It is higher when the boxes are exactly 17 bps apart. These findings can be partially explained by the flexibility of -35 boxes, which enables adjacent bases to create overlapping and new -35 boxes. Our work can help to engineer synthetic promoters for strength and robustness, and to understand the dynamics of promoter evolution.

evolutionary biology↗

bioRxiv2025

De-novo promoters emerge more readily from random DNA than from genomic DNA

Promoters are DNA sequences that help to initiate transcription. Point mutations can create de-novo promoters, which can consequently transcribe inactive genes or create novel transcripts. We know little about how de-novo promoters emerge in genomic DNA, especially compared to random DNA that has never been subjected to selection. Here, we assayed the promoter activity of 17,129 random, synthetic DNA sequences and 91,866 E. coli genomic DNA sequences. Genomic DNA encodes ~1.3 times more promoters than random DNA. We then studied 584,573 point mutations in 225 random and 60 genomic sequences, and asked how they cause the emergence of de-novo promoters. We find that de-novo promoters emerge ~3 times more readily from random DNA than from genomic DNA. The reason is that the genome contains fewer proto-binding sites for transcriptional activators than random DNA. Our work shows that the evolutionary history of a DNA sequence introduces substantial biases in its evolutionary potential, especially in the likelihood that mutations create new and potentially adaptive transcripts.

evolutionary biology↗

bioRxiv2025

Intergenic polyA/T tracts explain the propensity of yeast de novo genes to encode transmembrane domains

New genes can emerge de novo from non-genic genomic regions. In budding yeast, computational predictions have shown that intergenic regions harbor a higher-than-expected propensity to encode transmembrane domains, and this propensity seems to be linked to the high prevalence of predicted transmembrane domains in evolutionarily young genes. However, what accounts for this enriched propensity is not known. Here we show that specific arrangements of polyA/T tracts, which are abundant and enriched in yeast intergenic regions explain this observation. We provide evidence that polyA/T tracts, which are known to act as Nucleosome Depleted Regions in a regulatory context, have been coopted through de novo gene emergence for the evolution of novel small genes encoding proteins with predicted transmembrane domains. Our findings contribute to our understanding of the process of de novo gene evolution and show how seemingly distinct but interacting levels of functionality can exist within the same genomic loci.

genomics↗

bioRxiv2024

Spherical harmonics texture extraction for versatile analysis of biological objects

The characterization of phenotypes in cells or organisms from microscopy data largely depends on differences in the spatial distribution of image intensity. Multiple methods exist for quantifying the intensity distribution - or image texture - across objects in natural images. However, many of these texture extraction methods do not directly adapt to 3D microscopy data. Here, we present Spherical Texture extraction, which measures the variance in intensity per angular wavelength by calculating the Spherical Harmonics or Fourier power spectrum of a spherical or circular projection of the angular mean intensity of the object. This method provides a 20-value characterization that quantifies the scale of features in the spherical projection of the intensity distribution, giving a different signal if the intensity is, for example, clustered in parts of the volume or spread across the entire volume. We apply this method to different systems and demonstrate its ability to describe various biological problems through feature extraction. The Spherical Texture extraction characterizes biologically defined gene expression patterns in Drosophila melanogaster embryos, giving a quantitative read-out for pattern formation. Our method can also quantify morphological differences in Caenorhabditis elegans germline nuclei, which lack a predefined pattern. We show that the classification of germline nuclei using their Spherical Texture outperforms a convolutional neural net when training data is limited. Additionally, we use a similar pipeline on 2D cell migration data to extract polarization direction, quantifying the alignment of fluorescent markers to the migration direction. We implemented the Spherical Texture method as a plugin in ilastik, making it easy to install and apply to any segmented 3D or 2D dataset. Additionally, this technique can also easily be applied through a Python package to provide extra feature extraction for any object classification pipeline or downstream analysis. Author summaryWe introduce a novel method to extract quantitative data from microscopy images by precisely measuring the distribution of intensities within objects in both 3D or 2D. This method is easily accessible through the object classification workflow of ilastik, provided the original image is segmented into separate objects. The method is specifically designed to analyze mostly convex objects, focusing on the variation in fluorescence intensity caused by differences in their shapes or patterns. We demonstrate the versatility of our method by applying it to very different biological samples. Specifically, we showcase its effectiveness in quantifying the patterning in D. melanogaster embryos, in classifying the nuclei in C. elegans germlines, and in extracting polarization information from individual migratory cells. Through these examples, we illustrate that our technique can be employed across different biological scales. Furthermore, we highlight the multiple ways in which the data generated by our method can be used, including quantifying the strength of a specific pattern, employing machine learning to classify diverse morphologies, or extracting directionality or polarization from fluorescence intensity.

bioinformatics↗

bioRxiv2024

Promoter motifs facilitate as well as impede the emergence and evolution of gene expression

Gene regulation is essential for life and controlled by regulatory DNA. Mutations can modify the activity of regulatory DNA, and also create new regulatory DNA, a process called regulatory emergence. Non-regulatory and regulatory DNA contain motifs to which transcription factors may bind. In prokaryotes, gene expression requires a stretch of DNA called a promoter, which contains two motifs called -10 and -35 boxes. However, these motifs may occur in both promoters and non-promoter DNA in multiple copies. They have been implicated in some studies to improve promoter activity, and in others to repress it. Here, we ask whether the presence of such motifs in different genetic sequences influences promoter evolution and emergence. To understand whether and how promoter motifs influence promoter emergence and evolution, we start from 50 "promoter islands", DNA sequences enriched with -10 and -35 boxes. We mutagenize these starting "parent" sequences, and measure gene expression driven by 240000 of the resulting mutants. We find that the probability that mutations create an active promoter varies more than 200-fold, and is not correlated with the number of promoter motifs. For parent sequences without promoter activity, mutations created over 1500 new -10 and -35 boxes at unique positions in the library, but only [~]0.3% of these resulted in de-novo promoter activity. Only [~]13% of all -10 and -35 boxes contribute to de-novo promoter activity. For parent sequences with promoter activity, mutations create new -10 and -35 boxes in 11 specific positions that partially overlap with preexisting ones to modulate expression. We also find that -10 and -35 boxes do not repress promoter activity. Overall, our work demonstrates how promoter motifs influence promoter emergence and evolution. It has implications for predicting and understanding regulatory evolution, de-novo genes, and phenotypic evolution.

evolutionary biology↗

bioRxiv2023

Mobile DNA is replete with hotspots for the de novo emergence of gene regulation

Transposable elements can alter gene regulation in their host genome, either when they integrate into a genome, or when they accrue mutations after integration. However, the extent to which transposons can alter gene expression, as well as the necessary mutational steps, are not well characterized. Here we study the gene regulatory potential of the prominent IS3 family of transposable elements in E.coli. We started with 10 sequences from the ends of 5 IS3 sequences, created 18,537 random mutations in them, and measured their promoter activity using a massively parallel reporter assay. All 10 sequences could evolve de-novo promoter activity from single point mutations. De-novo promoters mostly emerge from existing proto-promoter sequences when mutations create new -10 boxes downstream of preexisting -35 boxes. The ends of IS3s harbor ~1.5 times as many such proto-promoter sequences than the E. coli genome. We also estimate that at least 26% of the 706 characterized IS3s already encode promoters. Our study shows that transposable elements can have a high latent cis-regulatory potential. Our observations can help to explain why mobile DNA may persist in prokaryotic genomes. They also underline the potential use of transposable elements as a substrate for evolving new gene expression.

evolutionary biology↗

bioRxiv2022

Mutational scans reveal differential evolvability of Drosophila promoters and enhancers

Rapid enhancer and slow promoter evolution have been demonstrated through comparative genomics. However, it is not clear how this information is encoded genetically and if this can be used to place evolution in a predictive context. Part of the challenge is that our understanding of the potential for regulatory evolution is biased primarily toward natural variation or limited experimental perturbations. Here, to explore the evolutionary capacity of promoter variation, we surveyed an unbiased mutation library for three promoters in Drosophila melanogaster. We found that mutations in promoters had limited to no effect on spatial patterns of gene expression. Compared to developmental enhancers, promoters are more robust to mutations and have more access to mutations that can increase gene expression, suggesting that their low activity might be a result of selection. Consistent with these observations, increasing the promoter activity at the endogenous locus of shavenbaby led to increased transcription yet limited phenotypic changes. Taken together, developmental promoters may encode robust transcriptional outputs allowing evolvability through the integration of diverse developmental enhancers. Quote"Regulators, mount up [at transcriptional promoters]." - Warren G & Nate Dogg, 1994

evolutionary biology↗

bioRxiv2022

Enhancer architecture and chromatin accessibility constrain phenotypic space during development

Developmental enhancers are DNA sequences that when bound to transcription factors dictate specific patterns of gene expression during development. It has been proposed that the evolution of such cis-regulatory elements is a major source of adaptive evolution; however, the regulatory and evolutionary potential of such elements remains little understood, masked by selective constraints, drift and contingency. Here, using mutation libraries in Drosophila melanogaster embryos, we observed that most mutations in classical developmental enhancers led to changes in gene expression levels but rarely resulted in novel expression outside of the native cell- and tissue-types. In contrast, random sequences often acted as developmental enhancers, driving expression across a range of levels and cell-types, in patterns consistent with transcription factor motifs therein; random sequences including motifs for transcription factors with pioneer activity acted as enhancers even more frequently and resulting in higher levels of expression. Together, our findings suggest that the adaptive phenotypic landscapes of developmental enhancers are constrained by both enhancer architecture and chromatin accessibility. We propose that the evolution of existing enhancers is limited in its capacity to generate novel phenotypes, whereas the activity of de novo elements is a primary source of phenotypic novelty. QUOTE"Chance and chance alone has a message for us." Milan Kundera, The Unbearable Lightness of Being

developmental biology↗

bioRxiv2020

Dense encoding of developmental regulatory information may constrain evolvability

Gene regulatory changes underlie much of phenotypic evolution. However, the evolutionary potential of regulatory evolution is unknown, because most evidence comes from either natural variation or limited experimental perturbations. Surveying an unbiased mutation library for a developmental enhancer in Drosophila melanogaster using an automated robotics pipeline, we found that most mutations alter gene expression. Our results suggest that regulatory information is distributed throughout most of a developmental enhancer and that parameters of gene expression--levels, location, and state--are convolved. The widespread pleiotropic effects of most mutations and the codependency of outputs may constrain the evolvability of developmental enhancers. Consistent with these observations, comparisons of diverse drosophilids reveal mainly stasis and apparent biases in the phenotypes influenced by this enhancer. Developmental enhancers may encode a much higher density of regulatory information than has been appreciated previously, which may impose constraints on regulatory evolution. Quote"Rock, robot rock Rock, robot rock Rock, robot rock" Daft Punk (2005)

evolutionary biology↗