Biology subjects

Fiston-Lavier, A.-S.

Publications and source records attributed to Fiston-Lavier, A.-S..

10 recordsLinked to original sources

bioRxiv2025

A scalable architecture for tuning multistate differentiation ratios in synthetic microbial consortia

Establishing synthetic microbial consortia in competitive environments is often compromised by stochastic colonization bottlenecks, where founder effects lead to the unpredictable dominance of a single strain. Here, we overcome this challenge by engineering a differentiation abacus, a scalable, single-layer recombinase architecture that enables a single progenitor cell to differentiate into up to twelve distinct subpopulations. By arranging competitive excision sites in a linear array, we demonstrate that differentiation ratios can be programmed through rationally tuning recombination-site kinetics and inter-site spacing. This architecture allows the generation of strictly mutually exclusive phenotypes with tunable composition, scaling from simple two-state systems to complex multi-state ensembles without the need for multilayered regulation. Finally, we validate the systems utility in a mouse tumor model, showing that in situ differentiation establishes robust, homogeneous consortia that overcome the colonization variability associated with pre-assembled mixtures. This work provides a versatile and scalable framework for reliably controlling consortia composition for bioproduction, synthetic ecology, and engineered living therapies.

synthetic biology↗

bioRxiv2025

Aridity shapes adaptive genomic divergence and population connectivity in a Southern African rodent

Elucidating the drivers of evolution in dry environments is central to understanding how organisms respond to climate change. While research on the genomics of adaptation is growing, aridity-driven intraspecific divergence remains poorly quantified. Here, we address this gap by using genomic data from 230 individuals of the arid-adapted four-striped mouse Rhabdomys bechuanae, sampled across an aridity gradient in southern Africa, a region facing increasing aridification. Combining these data with palaeoclimatic reconstructions and present-day aridity indices, we investigate, from a spatio-temporal perspective, how intraspecific genetic variation relates to aridity. Inference of past effective population size revealed a sharp decline in the late Pleistocene, coinciding with regional aridification and potentially reflecting changes in connectivity during dry periods. Current population structure followed a pattern of isolation by distance and mirrored the aridity gradient. Genotype-Environment Association analyses identified SNPs and genes significantly associated with aridity and genetically differentiated among populations, with functions related to water and energy conservation - as expected under arid conditions - as well as neurotransmission. These findings highlight the underappreciated role for neurological processes in coping with water and resource scarcity. More broadly, our integrative genomics approach suggests that aridity shapes population connectivity and adaptation, with implications for climate resilience.

genomics↗

bioRxiv2025

Manual versus automatic annotation of transposable elements: case studies in Drosophila melanogaster and Aedes albopictus, balancing accuracy and biological relevance

Transposable elements (TEs) play a pivotal role in genome evolution, yet their detection and annotation remain challenging due to the limitations of current methods. Manual curation is considered the gold standard for generating TE libraries, particularly for TE focused studies, although it requires extensive training and time. With the rapid increase in genome assembly publications and the growing need for large-scale comparative analyses, automated software for TE annotation has become indispensable. This study compares manual and automated approaches to TE detection and annotation, focusing on two species: Drosophila melanogaster and Aedes albopictus. In D. melanogaster, a species with a well-annotated TE repertoire and a smaller genome, the differences between manual curation (MCTE) and automated annotation (ATTE) are relatively minor. However, significant differences arise when analysing Ae. albopictus, a species with a larger genome and higher TE diversity. While automated methods identified a greater number of TEs, including many smaller and fragmented elements, manual curation provided more detailed classifications and on average larger consensi. Automated pipelines offer a viable alternative for genome-wide analyses such as TE content estimate, particularly when time and resources are limited. However, caution is advised when interpreting results, as finer details of TE dynamics may be overlooked. This study highlights that the choice of annotation method depends on the intended analysis. Manual curation is more suitable for TE population genomics and studies focusing on recent transposable element activity, while automated methods are appropriate for larger comparative analyses or genome assembly projects. Ultimately, both methods have their strengths and limitations, and understanding the specific features of the genome and repeatome under study is essential for selecting the appropriate approach.

genomics↗

bioRxiv2024

Effective population size does not explain long-term variation in genome size and transposable element content in animals

Animal genomes exhibit a remarkable variation in size, but the evolutionary forces responsible for such variation are still debated. As the effective population size (Ne) reflects the intensity of genetic drift, it is expected to be a key determinant of the fixation rate of nearly-neutral mutations. Accordingly, the Mutational Hazard Hypothesis postulates lineages with low Ne to have bigger genome sizes due to the accumulation of slightly deleterious transposable elements (TEs), and those with high Ne to maintain streamlined genomes as a consequence of a more effective selection against TEs. However, the existence of both empirical confirmation and refutation using different methods and different scales precludes ts general validation. Using high-quality public data, we estimated genome size, TE content and rate of non-synonymous to synonymous substitutions (dN/dS) as Ne proxy for 807 species including vertebrates, molluscs and insects. After collecting available life-history traits, we tested the associations among population size proxies, TE content and genome size, while accounting for phylogenetic non-independence. Our results confirm TEs as major drivers of genome size variation, and endorse life-history traits and dN/dS as reliable proxies for Ne. However, we do not find any evidence for increased drift to result in an accumulation of TEs across animals. Within more closely related clades, only a few isolated and weak associations emerge in fishes and birds. Our results outline a scenario where TE dynamics vary according to lineage-specific patterns, lending no support for genetic drift as the predominant force driving long-term genome size evolution in animals.

evolutionary biology↗

bioRxiv2022

TrEMOLO: Accurate transposable element allele frequency estimation using long-read sequencing data combining assembly and mapping-based approaches

Transposable Element MOnitoring with LOng-reads (TrEMOLO) is a new software that combines assembly- and mapping-based approaches to robustly detect genetic elements called transposable elements (TEs). Using high- or low-quality genome assemblies, TrEMOLO can detect most TE insertions and deletions and estimate their allele frequency in populations. Benchmarking with simulated data revealed that TrEMOLO outperforms other state-of-the-art computational tools. TE detection and frequency estimation by TrEMOLO were validated using simulated and experimental datasets. Therefore, TrEMOLO is a comprehensive and suitable tool to accurately study TE dynamics. TrEMOLO is available under GNU GPL3.0 at https://github.com/DrosophilaGenomeEvolution/TrEMOLO.

bioinformatics↗

bioRxiv2022

RF4Del: A Random Forest approach for accurate deletion detection

Efficiently detecting genomic structural variants (SVs) is a key step to grasp the "missing heritability" underlying complex traits involved in major evolutionary processes such as speciation, phenotypic plasticity, and adaptive responses. Yet, the SV-based genotype/trait association studies are still largely overlooked mainly due to the lack of reliable detection methods. Here, we present a random forest (RF) method for accurate deletion identification: RF4Del. By relying on the analysis of the mapping profiles, data already available in most sequencing projects, RF4Del can easily and quickly call deletions. Several classic and ensemble learning strategies were carefully evaluated using proper benchmark data. RF4Del was trained and tested on simulated data from the model species Drosophila melanogaster to detect deletions. The model consists of 13 features extracted from a mapping file. We show that RF4Del outperforms established SV callers (DELLY, Pindel) with higher overall performance (F1-score > 0.75; 6x-12x sequence coverage) and is less affected by low sequencing coverage and deletion size variations. RF4Del could learn from a compilation of sequence patterns linked to a given SV. Such models can then be combined to form a learning system able to detect all types of SVs in a given genome, beyond the one used in our study. https://github.com/alvesrcoo/eletric-scheep

bioinformatics↗

bioRxiv2022

Structural variation turnovers and defective genomes: key drivers for the in vitro evolution of the large double-stranded DNA koi herpesvirus (KHV)

AO_SCPLOWBSTRACTC_SCPLOWStructural variations (SVs) constitute a significant source of genetic variability in virus genomes. Yet knowledge about SV variability and contribution to the evolutionary process in large double-stranded (ds)DNA viruses is limited. Cyprinid herpesvirus 3 (CyHV-3), also commonly known as koi herpesvirus (KHV), has the largest dsDNA genome within herpesviruses. This virus has become one of the biggest threats to common carp and koi farming, resulting in high morbidity and mortalities of fishes, serious environmental damage, and severe economic losses. A previous study analyzing CyHV-3 virulence evolution during serial passages onto carp cell cultures suggested that CyHV-3 evolves, at least in vitro, through an assembly of haplotypes that alternatively become dominant or under-represented. The present study investigates the SV diversity and dynamics in CyHV-3 genome during 99 serial passages in cell culture using, for the first time, ultra-deep whole-genome and amplicon-based sequencing. The results indicate that KHV polymorphism mostly involves SVs. These SVs display a wide distribution along the genome and exhibit high turnover dynamics with a clear bias towards inversion and deletion events. Analysis of the pathogenesis-associated ORF150 region in ten intermediate cell passages highlighted mainly deletion, inversion and insertion variations that deeply altered the structure of ORF150. Our findings indicate that SV turnovers and defective genomes represent key drivers in the viral population dynamics and in vitro evolution of KHV. Thus, the present study can contribute to the basic research needed to design safe live-attenuated vaccines, classically obtained by viral attenuation after serial passages in cell culture.

genomics↗

bioRxiv2020

PlasForest: a homology-based random forest classifier for plasmid detection in genomic datasets

Plasmids are mobile genetic elements that often carry accessory genes, and are vectors for horizontal transfer between bacterial genomes. The detection of plasmids in large sets of genomes is crucial to analyze their spread and quantify their role in bacteria adaptation and particularly in antibiotic resistance genes propagation. Several bioinformatics methods have been developed to detect plasmids. However, they suffer from low sensitivity (i.e., most plasmids remain undetected) or low precision (i.e., these methods identify chromosomes as plasmids), and are overall not adapted to identify plasmids in whole genomes that are not fully assembled (contigs and scaffolds). Here, we present PlasForest, a homology-based random forest classifier identifying bacterial plasmid sequences in unassembled genomes. This tool is based on the determination of homologies against a database of plasmid sequences, which allow a random forest classifier to discriminate plasmid contigs. Without knowing the taxonomical origin of the samples, PlasForest identifies contigs as plasmids or chromosomes with an accuracy of 98%. Notably, it can detect 96% of plasmid contigs over 50kb with 3.3% of false positives. PlasForest outperforms other currently available tools on test datasets by being both sensitive and precise. We implemented this tool in a user-friendly pipeline that can identify plasmids in large datasets in a reasonable amount of time.

genomics↗

bioRxiv2019

Machine learning reveals bilateral distribution of somatic L1 insertions in human neurons and glia

Active retrotransposons in the human genome (L1, Alu and SVA elements) can create genomic mobile element insertions (MEIs) in both germline and somatic tissue1. Specific somatic MEIs have been detected at high levels in human cancers2, and at lower to medium levels in human brains3. Dysregulation of somatic retrotransposition in the human brain has been hypothesized to contribute to neuropsychiatric diseases4, 5. However, individual somatic MEIs are present in small proportions of cells at a given anatomical location, and thus standard whole-genome sequencing (WGS) presents a difficult signal-to-noise problem, while single-cell approaches suffer from limited scalability and experimental artifacts introduced by enzymatic whole-genome amplification6. Previous studies produced widely differing estimates for the somatic retrotransposition rates in human brain3, 6-8. Here, we present a highly precise machine learning method (RetroSom) to directly identify somatic L1 and Alu insertions in <1% cells from 200x deep WGS, which allows circumventing the restrictions of whole-genome amplification. Using RetroSom we confirmed a lower rate of retrotransposition for individual somatic L1 insertions in human neurons. We discovered that anatomical distribution of somatic L1 insertion is as widespread in glia as in neurons, and across both hemispheres of the brain, indicating retrotransposition occurs during early embryogenesis. We characterized two of the detected brain-specific L1 insertions in great detail in neurons and glia from a donor with schizophrenia. Both insertions are within introns of genes active in brain (CNNM2, FRMD4A) in regions with multiple genetic associations with neuropsychiatric disorders9-11. Gene expression was significantly reduced by both somatic insertions in a reporter assay. Our results provide novel insights into the potential for pathological effects of somatic retrotransposition in the human brain, now including the large glial fraction. RetroSom has broad applicability in all disease states where somatic retrotransposition is expected to play a role, such as autoimmune disorders and cancer.

bioinformatics↗

bioRxiv2018

Stress response, behavior, and development are shaped by transposable element-induced mutations in Drosophila

Mapping genotype to phenotype is challenging because of the difficulties in identifying both the traits under selection and the specific genetic variants underlying these traits. Most of the current knowledge of the genetic basis of adaptive evolution is based on the analysis of single nucleotide polymorphisms (SNPs). Despite increasing evidence for their causal role, the contribution of structural variants to adaptive evolution remains largely unexplored. In this work, we analyzed the population frequencies of 1,615 Transposable Element (TE) insertions in 91 samples from 60 worldwide natural populations of Drosophila melanogaster. We identified a set of 300 TEs that are present at high population frequencies, and located in genomic regions with high recombination rate, where the efficiency of natural selection is high. The age and the length of these 300 TEs are consistent with relatively young and long insertions reaching high frequencies due to the action of positive selection. Indeed, we, and others, found evidence of selective sweeps and/or population differentiation for 65 of them. The analysis of the genes located nearby these 65 candidate adaptive insertions suggested that the functional response to selection is related with the GO categories of response to stimulus, behavior, and development. We further showed that a subset of the candidate adaptive TEs affect expression of nearby genes, and five of them have already been linked to an ecologically relevant phenotypic effect. Our results provide a more complete understanding of the genetic variation and the fitness-related traits relevant for adaptive evolution. Similar studies should help uncover the importance of TE-induced adaptive mutations in other species as well.

evolutionary biology↗