Biology subjects

Schikora-Tamarit, M. A.

Publications and source records attributed to Schikora-Tamarit, M. A..

5 recordsLinked to original sources

bioRxiv2026

Ancient whole genomes reveal regional selection during adaptation to Neolithic lifestyle in Western Eurasia

The introduction of agriculture in Western Eurasia during the Mesolithic-Neolithic transition reshaped human lifestyle, demography and pathogen exposure. Yet, the associated selective pressures remain incompletely resolved because previous ancient DNA studies relied on targeted SNP panels and yielded non-overlapping results. Here, using high-coverage whole-genome data from 152 ancient individuals, including 12 newly sequenced genomes from the Iron Gates, we show that adaptation during this transition was geographically structured and involved selection of both Early Farmer and Hunter-Gatherer alleles. By combining scans of population differentiation, extended haplotype homozygosity, and adaptive admixture, we identify candidate loci under selection in ancestral and admixed populations. Extending the analysis beyond SNPs, we also detect differential copy-number variants, ancestry-associated shifts in transposable-element abundance, and an early Neolithic hepatitis B infection. Functional analyses including effects on gene expression suggested selection on immune, metabolic, reproductive, sensory, and behavioural processes. Taken together, our results reveal a broader and more regionally variable adaptive landscape than previously appreciated.

evolutionary biology↗

bioRxiv2026

Reversible haploidisation and convergent genomic routes to antifungal resistance in the Candida parapsilosis species complex

Antifungal resistance is rising among non-albicans Candida, with outbreaks increasingly linked to drug-resistant Candida parapsilosis. Using large-scale experimental evolution under fluconazole and anidulafungin, coupled to phenotyping and genome sequencing, we define resistance strategies across C. parapsilosis, Candida metapsilosis and Candida orthopsilosis. Despite diverse genetic backgrounds, adaptation repeatedly converged on a shared genomic toolkit that combines protein-altering mutations in key regulators and drug targets (including MRR1 and FKS1) with copy-number changes, aneuploidy, as well as loss of heterozygosity driving resistance alleles to homozygosity. Strikingly, drug selection triggered recurrent but reversible haploidisation in C. orthopsilosis, revealing ploidy reduction as a transient, selectable survival strategy. Resistance, particularly after fluconazole selection, imposed fitness costs that promoted compensatory evolution and resistance loss after drug withdrawal. Together, antifungal adaptation in this complex affects convergent targets, while being plastic in its genomic routes, with implications for resistance surveillance and drug cycling therapies.

microbiology↗

bioRxiv2026

Dissection of genotype-phenotype relationships in Candida parapsilosis uncovers drivers of clinically-relevant traits

Hospital outbreaks caused by the fungal pathogen Candida parapsilosis are of growing concern due to their increased drug resistance and high mortality rates. However, the genetic bases of clinically-relevant traits in this species remain poorly explored. Here, we mapped genotype-phenotype relationships across 189 isolates from a multi-hospital Candida parapsilosis outbreak, for which we measured 61 diverse clinical phenotypes and generated complete genome sequences. As variation in previously-known genes explained little of the observed phenotypic diversity, we leveraged convergence genome-wide association studies and interpretable machine-learning models that predict phenotypes from genetic variants. These approaches identified candidate drivers of virulence and antifungal resistance, confirming expected mechanisms while uncovering novel ones. Predictive models were accurate for key traits, including azole resistance and clinical features of infected patients. Our results shed light on the genetic bases of clinically-relevant traits in a major fungal pathogen, and pave the way towards sequence-based diagnostics for improved patient outcomes.

microbiology↗

bioRxiv2021

PerSVade: Personalized Structural Variation detection in your species of interest

Structural variants (SVs) like translocations, deletions, and other rearrangements underlie genetic and phenotypic variation. SVs are often overlooked due to difficult detection from short-read sequencing. Most algorithms yield low recall on humans, but the performance in other organisms is unclear. Similarly, despite remarkable differences across species genomes, most approaches use parameters optimized for humans. To overcome this and enable species-tailored approaches, we developed perSVade (personalized Structural Variation Detection), a pipeline that identifies SVs in a way that is optimized for any input sample. Starting from short reads, perSVade uses simulations on the reference genome to choose the best SV calling parameters. The output includes the optimally-called SVs and the accuracy, useful to assess the confidence in the results. In addition, perSVade can call small variants and copy-number variations. In summary, perSVade automatically identifies several types of genomic variation from short reads using sample-optimized parameters. We validated that perSVade increases the SV calling accuracy on simulated variants for six diverse eukaryotes, and on datasets of validated human variants. Importantly, we found no universal set of "optimal" parameters, which underscores the need for species-specific parameter optimization. PerSVade will improve our understanding about the role of SVs in non-human organisms.

bioinformatics↗

bioRxiv2017

Promoter activity buffering reduces the fitness cost of misregulation.

O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY\n\nIn BriefSystematic promoter replacement reveals that coding sequences and 3ends of genes play and active role in buffering cells from fitness defects due to misregulation.\n\nHighlightsO_LIThe TF dose-response curve -- how gene expression changes as a function of TF concentration -- is encoded throughout the gene, not only in the promoter. Genes with the same promoter have different TF DRCs.\nC_LIO_LIA coupled experimental system and mathematical model quantifies the intrinsic ability of genes to buffer or amplify promoter activity.\nC_LIO_LIPromoter activity buffering reduces the effect of misregulation on fitness.\nC_LI\n\nCells regulate gene expression by changing the concentration and activity of transcription factors (TFs). The response of each gene to changes in TF activity is generally assumed to be encoded in the promoter. Here we show that, even when the promoter itself remains constant, each gene has a unique TF dose response curve. Genes have an intrinsic ability to either buffer or amplify the effects of high promoter activity. We present a coupled mathematical model and experimental system for quantifying this property. Promoter activity buffering can be encoded by sequences in both the open reading frame and 3end of genes, and can be implemented by both autoregulatory feedback loops and by titration of limiting trans regulators. We show experimentally that promoter activity buffering insulates cells from fitness defects due to misexpression. The response of genes to changes in [TF] is encoded by sequences outside of the promoter, and this effect can either insulate or amplify the effects of aneuploidy and misregulation on organismal fitness.

systems biology↗